Anthropic is a U.S.-based artificial intelligence (AI) research and development company founded by former OpenAI members. Specializing in language models and information systems, Anthropic is committed to advancing AI with a strong focus on responsible and ethical use. The company offers career opportunities for ML engineers, software engineers and research engineers to help shape the future of trustworthy AI technology.

anthropic

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.About the Role At Anthropic, we believe new AI capabilities are best achieved through secure foundations, not in spite of them. As capabilities grow more advanced, it is critical that progress moves forward safely and for the benefit of all society. It is the reason why security sits at the center of our work, and not as an afterthought. We're specifically looking for a Software Engineer with deep Windows expertise to help us build and maintain Claude Code, our AI-powered coding assistant. The ideal candidate will have a passion for developer tools, strong experience building CLI applications on Windows, and a desire to ensure Windows developers have a first-class experience with our tools. Claude Code is used by developers around the world, and a significant portion of them work in Windows environments. This role is critical to ensuring our product works seamlessly for Windows users—from installation to daily workflows. &nbsp; Responsibilities Design, build, and maintain Windows-specific features and infrastructure for Claude Code Own the Windows developer experience, ensuring Claude Code installs, runs, and performs reliably across Windows environments Develop and maintain PowerShell integrations and scripts that enable smooth Windows workflows Collaborate with the broader Claude Code team to ensure cross-platform compatibility and feature parity Work with Windows package managers (Chocolatey, winget, scoop) to streamline installation and updates for Windows users Debug and resolve Windows-specific issues, including file system, permissions, and shell compatibility challenges Engage directly with Windows developers inside and outside Anthropic to gather feedback and improve user experience Contribute to technical documentation to help Windows users get the most out of Claude Code &nbsp; You May Be a Good Fit If You Have deep Windows development experience, including PowerShell scripting and Windows system integration Have experience building and maintaining CLI applications Are passionate about developer tools and understand what makes tools useful and adoptable Can work independently to identify and solve Windows-specific challenges Have shipped software used by developers in production Windows environments Care about the societal impacts and ethics of your work &nbsp; Strong Candidates May Also Have Experience With Have strong TypeScript development experience Linux and/or macOS development (cross-platform thinking) Cross-platform compatibility considerations and tooling Windows package managers (Chocolatey, winget, scoop) Working with large codebases and quickly jumping into unfamiliar development environments Working with container orchestration and cloud infrastructure (especially Windows containers) Hands-on experience working with large language models and prompt engineering Node.js/Bun runtime environments Building and maintaining developer tools at scale &nbsp; Why Join Anthropic? This is an opportunity to shape the future of AI-driven development tools while working alongside top engineers and researchers in the field. You'll play a key role in ensuring Claude Code delivers an exceptional experience for the millions of developers who work on Windows every day.The annual compensation range for this role is listed below.&nbsp; For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.Annual Salary:$320,000&mdash;$485,000 USDLogistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship:&nbsp;We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.&nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from&nbsp;@anthropic.com&nbsp;email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit&nbsp;anthropic.com/careers&nbsp;directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage:&nbsp;Learn about&nbsp;our policy&nbsp;for using AI in our application process

Software Engineer, Windows - Claude Code

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.Anthropic's Reinforcement Learning organization leads the research and development that trains Claude to be capable, reliable, and safe. We've contributed to every Claude model, with significant impacts on the autonomy and coding capabilities of our most advanced models. Our work spans developing systems that enable models to use computers effectively, advancing code generation through reinforcement learning, pioneering fundamental RL research for large language models, and building scalable training methodologies. The RL org is organized around four key goals: solving the science of long-horizon tasks and continual learning, scaling RL data and environments to be comprehensive and diverse, automating software engineering end-to-end, and training the frontier production model. We collaborate closely with Anthropic's alignment and safety teams to ensure our systems are both capable and safe. Our engineering teams build the environments, evaluation systems, data pipelines, and tooling that make all of this possible: from realistic agentic training environments and scalable code data generation, to human data collection platforms and production training operations. About the Role As a Full-Stack Software Engineer within Reinforcement Learning, you'll build the platforms, tools, and interfaces that power RL environment creation, data collection, and training observability. Our ability to train frontier models depends on generating diverse, high-quality training data — and the products you build are what make that possible for researchers, vendors, and data labelers alike. This is a software engineering role embedded within research teams. You'll own product surfaces end-to-end — from backend services and APIs to web UIs that internal researchers, external vendors, and data labelers rely on daily. You don't need a background in ML research — what matters is strong full-stack engineering skills and the ability to build polished, reliable products in a fast-moving environment. What You'll Do: Build and extend web platforms for RL environment creation, management, and quality review — including environment configuration, versioning, and validation workflows Develop vendor-facing interfaces and tooling that enable external partners to create, submit, and iterate on training environments with minimal friction Design and implement platforms for human data collection at scale, including labeling workflows, quality assurance systems, and feedback mechanisms Build evaluation dashboards and observability UIs that give researchers real-time insight into environment quality, training run health, and reward signal integrity Create backend services and APIs that connect environment authoring tools, data collection systems, and RL training infrastructure Build and expand scalable code data generation pipelines, creating diverse programming tasks with robust reward signals across languages and difficulty levels Develop onboarding automation and documentation tooling so new vendors and internal users can ramp up quickly Collaborate with RL researchers, data operations, and vendor management teams to translate their needs into well-designed product experiences You May Be a Good Fit If You: Have strong software engineering fundamentals with full-stack experience Are proficient in Python and modern web frameworks (React, TypeScript, or similar) Have experience building and shipping user-facing products, internal tools, or developer platforms Can own a product surface end-to-end — backend, frontend, API design, database schema Have experience with relational databases, API design patterns, and authentication/authorization systems Care about UX and can build interfaces that are intuitive for both technical and non-technical users Communicate clearly with researchers, operations teams, and engineers and can translate ambiguous requirements into well-scoped work Are motivated by building excellent platforms Operate with high agency: you identify what needs to be done and drive it forward independently Thrive in a fast-paced environment where priorities shift and new problems emerge regularly Care about Anthropic's mission to build safe, beneficial AI and want your work to contribute to that goal Strong Candidates May Also Have: Experience building data collection, labeling, or annotation platforms Background building multi-tenant platforms with role-based access and vendor management workflows Experience with cloud infrastructure (GCP or AWS), Docker, and CI/CD pipelines Familiarity with LLM training, fine-tuning, or evaluation workflows Experience with async Python frameworks (Trio, asyncio) or high-throughput API design Background building dashboards, monitoring, or observability tooling Experience working with external vendors or partners on technical integrations Representative Projects: Building a unified platform for human data collection that integrates labeling workflows, vendor management, and quality assurance for complex agentic tasks Developing vendor onboarding automation that handles Docker registry access, API token management, and environment validation Creating evaluation and observability dashboards that catch reward hacks, measure environment difficulty, and provide real-time feedback during production training Building environment quality review workflows that allow researchers to browse, grade, and provide feedback on training environments Developing automated environment quality pipelines that validate correctness and difficulty calibration before deployment to production training Building internal tools for browsing and analyzing training run results, environment statistics, and data collection progress The annual compensation range for this role is listed below.&nbsp; For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.Annual Salary:$300,000&mdash;$405,000 USDLogistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship:&nbsp;We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.&nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from&nbsp;@anthropic.com&nbsp;email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit&nbsp;anthropic.com/careers&nbsp;directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage:&nbsp;Learn about&nbsp;our policy&nbsp;for using AI in our application process

Full Stack Software Engineer, Reinforcement Learning

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.About the Role Anthropic is seeking talented and experienced Software Engineers to join our Builds team within the Developer Platform organization. The Builds team owns the build infrastructure that every engineer and researcher at Anthropic depends on—from hermetic build environments and container image pipelines to remote build execution, build caching, and dependency management across our monorepo. By joining this team, you'll have a direct impact on the velocity and reliability of Anthropic's research and product development. As Anthropic scales its engineering organization, research ambitions, and the volume of code contributed by both humans and AI agents, build infrastructure is becoming a critical bottleneck and a critical lever. We're building next-generation systems—scalable remote build execution with content-addressable storage, fine-grained incremental builds, and hermetic reproducible environments—to ensure that build times shrink even as the codebase grows by orders of magnitude. Our monorepo spans Python, Rust, and Go, with builds targeting multiple accelerator platforms (TPUs, Trainium, GPUs) and complex SDK dependencies. This creates uniquely challenging problems in hermeticity, caching, cross-language interop, and dependency management that few organizations encounter. If you've built or operated large-scale, hermetic build infrastructure at a company with a large monorepo and are excited about designing systems that keep thousands of engineers productive, this is the role for you. Responsibilities Design and build scalable, hermetic build infrastructure including remote build execution (RBE) and content-addressable storage (CAS) systems that support all source and image builds Own and evolve Nix-based build environments and package management, keeping nixpkgs and language runtimes current and compatible Drive fine-grained dependency management across the monorepo to enable incremental builds and eliminate unnecessary rebuilds Build and maintain language-specific build toolchains and accelerator SDK/runtime builds Reduce container image build times through architectural improvements to build pipelines, layer caching, and content-addressable storage Partner with CI, Languages, and Developer Acceleration teams to ensure build infrastructure integrates seamlessly with the broader developer platform You May Be a Good Fit If You: Have 6+ years of relevant industry experience building and operating large-scale build systems and infrastructure Have deep experience with hermetic, reproducible build systems (Bazel, Buck, Nix, or similar) in a large monorepo environment Understand build caching strategies, remote execution, and content-addressable storage deeply Have experience with containerized build environments and image build pipelines Have strong proficiency in at least one of Python, Rust, or Go Have excellent communication skills and enjoy supporting internal partners to improve their development experience Are excited about designing foundational systems and are comfortable working independently on ambiguous, high-impact technical challenges Strong Candidates May Also Have: Experience with Nix/NixOS and managing large Nix package sets at scale Experience with Rust build toolchains (cargo, maturin) and Python-Rust interop Experience building or operating remote build execution systems (Bazel Remote Execution API, BuildBarn, BuildBuddy, or similar) Experience managing accelerator SDK builds (CUDA, Neuron SDK, JAX/XLA) Experience with fine-grained dependency graph analysis and incremental build optimization at monorepo scale Deadline to apply: None. Applications will be reviewed on a rolling basis.The annual compensation range for this role is listed below.&nbsp; For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.Annual Salary:$320,000&mdash;$485,000 USDLogistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship:&nbsp;We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.&nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from&nbsp;@anthropic.com&nbsp;email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit&nbsp;anthropic.com/careers&nbsp;directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage:&nbsp;Learn about&nbsp;our policy&nbsp;for using AI in our application process

Senior Software Engineer, Build Systems

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.About the Role Anthropic is seeking talented and experienced Software Engineers to join our Builds team within the Developer Platform organization. The Builds team owns the build infrastructure that every engineer and researcher at Anthropic depends on—from hermetic build environments and container image pipelines to remote build execution, build caching, and dependency management across our monorepo. By joining this team, you'll have a direct impact on the velocity and reliability of Anthropic's research and product development. As Anthropic scales its engineering organization, research ambitions, and the volume of code contributed by both humans and AI agents, build infrastructure is becoming a critical bottleneck and a critical lever. We're building next-generation systems—scalable remote build execution with content-addressable storage, fine-grained incremental builds, and hermetic reproducible environments—to ensure that build times shrink even as the codebase grows by orders of magnitude. Our monorepo spans Python, Rust, and Go, with builds targeting multiple accelerator platforms (TPUs, Trainium, GPUs) and complex SDK dependencies. This creates uniquely challenging problems in hermeticity, caching, cross-language interop, and dependency management that few organizations encounter. If you've built or operated large-scale, hermetic build infrastructure at a company with a large monorepo and are excited about designing systems that keep thousands of engineers productive, this is the role for you. Responsibilities Design and build scalable, hermetic build infrastructure including remote build execution (RBE) and content-addressable storage (CAS) systems that support all source and image builds Own and evolve Nix-based build environments and package management, keeping nixpkgs and language runtimes current and compatible Drive fine-grained dependency management across the monorepo to enable incremental builds and eliminate unnecessary rebuilds Build and maintain language-specific build toolchains and accelerator SDK/runtime builds Reduce container image build times through architectural improvements to build pipelines, layer caching, and content-addressable storage Partner with CI, Languages, and Developer Acceleration teams to ensure build infrastructure integrates seamlessly with the broader developer platform You May Be a Good Fit If You: Have 10+ years of relevant industry experience building and operating large-scale build systems and infrastructure Have deep experience with hermetic, reproducible build systems (Bazel, Buck, Nix, or similar) in a large monorepo environment Understand build caching strategies, remote execution, and content-addressable storage deeply Have experience with containerized build environments and image build pipelines Have strong proficiency in at least one of Python, Rust, or Go Have excellent communication skills and enjoy supporting internal partners to improve their development experience Are excited about designing foundational systems and are comfortable working independently on ambiguous, high-impact technical challenges Strong Candidates May Also Have: Experience with Nix/NixOS and managing large Nix package sets at scale Experience with Rust build toolchains (cargo, maturin) and Python-Rust interop Experience building or operating remote build execution systems (Bazel Remote Execution API, BuildBarn, BuildBuddy, or similar) Experience managing accelerator SDK builds (CUDA, Neuron SDK, JAX/XLA) Experience with fine-grained dependency graph analysis and incremental build optimization at monorepo scale Deadline to apply: None. Applications will be reviewed on a rolling basis.The annual compensation range for this role is listed below.&nbsp; For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.Annual Salary:$405,000&mdash;$485,000 USDLogistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship:&nbsp;We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.&nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from&nbsp;@anthropic.com&nbsp;email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit&nbsp;anthropic.com/careers&nbsp;directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage:&nbsp;Learn about&nbsp;our policy&nbsp;for using AI in our application process

Staff Software Engineer, Build Systems

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.Software Engineer (Model Quality), Claude Code San Francisco, CA or New York, NY About Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role We're looking for a Software Engineer to work at the intersection of engineering and research on the Claude Code team. In this role, you'll collaborate directly with Anthropic's researchers to improve Claude’s coding capabilities through tooling, infrastructure, and evaluations. You'll build systems that help us understand where Claude Code excels and where it falls short—and then help close those gaps. We're looking for engineers who can build robust, complex systems and who thrive in fast-paced, high-intensity environments. You'll take ambiguous problems and turn them into reliable infrastructure that accelerates our research. Responsibilities Design and build eval systems that measure model capabilities across diverse coding tasks Build tooling and infrastructure that enables researchers to run experiments at scale Develop pipelines for data collection, processing, and analysis Create internal tools that improve researcher productivity and accelerate iteration cycles Serve as a bridge between product and research—bring strong product intuition to inform which capabilities matter most Work closely with researchers to translate research questions into engineering solutions Own systems end-to-end—from design through production reliability You may be a good fit if you: Have built and owned complex systems—pipelines, infrastructure, or software that orchestrates many components and handles significant state and logic Thrive in high-intensity environments with fast iteration cycles Take full ownership of problems and drive them to completion independently Are a power user of agentic coding tools and have strong intuition about model capabilities and limitations Are comfortable diving into unfamiliar technical domains and figuring things out quickly Care deeply about correctness and reliability in the systems you build Are excited to work at the boundary between engineering and AI research Have at least 5 years of work experience Strong candidates may also have experience with: Writing or maintaining eval frameworks Reinforcement learning systems Working in high-performance, demanding environments—trading firms, quant funds, competitive research labs, or fast-moving startups where intensity is the norm Have research computing or scientific infrastructure background Have a strong quantitative foundation (math, physics, or related fields) Python and TypeScript The annual compensation range for this role is listed below.&nbsp; For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.Annual Salary:$320,000&mdash;$485,000 USDLogistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship:&nbsp;We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.&nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from&nbsp;@anthropic.com&nbsp;email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit&nbsp;anthropic.com/careers&nbsp;directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage:&nbsp;Learn about&nbsp;our policy&nbsp;for using AI in our application process

Model Quality Software Engineer, Claude Code

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.About the role Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators.&nbsp;The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. As a Staff Software Engineer on our Inference team, you will work end to end, identifying and addressing key infrastructure blockers to serve Claude to millions of users while enabling breakthrough AI research. Strong candidates should have familiarity with performance optimization, distributed systems, large-scale service orchestration, and intelligent request routing. Familiarity with LLM inference optimization, batching strategies, and multi-accelerator deployments is highly encouraged but not strictly necessary. Strong candidates may also have experience with High-performance, large-scale distributed systems Implementing and deploying machine learning systems at scale Load balancing, request routing, or traffic management systems LLM inference optimization, batching, and caching strategies Kubernetes and cloud infrastructure (AWS, GCP) Python or Rust You may be a good fit if you Have significant software engineering experience, particularly with distributed systems Are results-oriented, with a bias towards flexibility and impact Pick up slack, even if it goes outside your job description Want to learn more about machine learning systems and infrastructure Thrive in environments where technical excellence directly drives both business results and research breakthroughs Care about the societal impacts of your work Representative projects across the org Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads Building production-grade deployment pipelines for releasing new models to millions of users Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage Contributing to new inference features (e.g., structured sampling, prompt caching) Supporting inference for new model architectures Analyzing observability data to tune performance based on real-world production workloads Managing multi-region deployments and geographic routing for global customers Deadline to apply: None. Applications will be reviewed on a rolling basis.The annual compensation range for this role is listed below.&nbsp; For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.Annual Salary:£325,000&mdash;£390,000 GBPLogistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship:&nbsp;We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.&nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from&nbsp;@anthropic.com&nbsp;email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit&nbsp;anthropic.com/careers&nbsp;directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage:&nbsp;Learn about&nbsp;our policy&nbsp;for using AI in our application process

Staff Software Engineer, Inference

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.About the role Anthropic is dedicated to developing AI assistants that are helpful, harmless, and honest. As usage of our AI services grows, we need to ensure they are not misused. The Safeguards team is at the forefront of protecting our users from the risks of powerful AIs as well as ethical, technical, and social risks from the use of generative AI. The Safeguards team at Anthropic builds protections for new AI features enabled by the research teams and protects new products and surfaces developed by our product teams. As a Product Manager for the Safeguards team at Anthropic, you will own the ideation, design, development and deployment of Safeguards systems and relevant product UX to ensure we are advancing frontier models safely to users across various cloud platforms. You will work closely with our research and product teams to develop detections, evals, interventions, and tools to measure and mitigate deployment and user risks.&nbsp; We are looking for a product manager who is deeply committed to making AI safe and beneficial for humanity.&nbsp; You are aware of the risks and are committed to working with experts and coming up with ideas for Anthropic to implement. You have deep technical expertise in development, deployment and measurement of Safeguards systems. You thrive in rapidly moving and ambiguous environments. Responsibilities: Determine how to build in safety by design upstream and leverage downstream defenses for Anthropic’s frontier models, AI products, customers on different surfaces - Claude.ai, 1P API, external Cloud providers.&nbsp; Ability to write safety evals and communicate externally about safety.&nbsp; Drive impact via ruthless prioritization by clearly defining problems, solution options forward, clarity on both business &amp; technical tradeoffs and accordingly clear requirements toward MVP vs. ideal state. Align &amp; collaborate with policy, enforcement, research, engineering and cross functional stakeholders.&nbsp; Understand the AI landscape and ecosystem to plan for mitigation of deployment risks of increasingly powerful models and determined adversaries. Lead the development of metrics to understand the area, performance, blindspots to help inform future project planning. You may be a good fit if you have: 5+ years in product management with a focus on fast problem understanding, building roadmaps with tractable progress, ability to get into the details on data, detection &amp; interventions, infrastructure &amp; tools, and/or evals. Ability to make technical tradeoff decisions; ideally with experience working across policy experts, AI/ML research engineers and software engineering teams to design and build state of the art safety systems.&nbsp; Strong user understanding of how our products are used, their Safeguards concerns and how we provide the best solutions. Demonstrated ability to build product and engineering strategy across multiple cross-functional teams for a rapidly changing space. Demonstrated experience in designing and building metrics to evaluate risks, system performance, user impact and making crisp tradeoffs Very strong ability to navigate, and prioritize amidst rapidly changing product specs, and to flex into different domains to bring clarity and execute.&nbsp; Evidence of exercising judgment and decision making in ambiguous situations. Planning, building, launching and measuring new products / systems in a zero to one environment. Ability to clearly articulate complex technical concepts to non-technical audiences in written and verbal communication. Think creatively about the risks and benefits of new technologies, and think beyond past checklists and playbooks. The annual compensation range for this role is listed below.&nbsp; For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.Annual Salary:$305,000&mdash;$385,000 USDLogistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship:&nbsp;We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.&nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from&nbsp;@anthropic.com&nbsp;email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit&nbsp;anthropic.com/careers&nbsp;directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage:&nbsp;Learn about&nbsp;our policy&nbsp;for using AI in our application process

Product Manager, Safeguards (Beneficial Deployment)

Product Manager, Safeguards (Privacy)

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.About the role The AIRE Serving team is responsible for elevating the reliability of Anthropic’s token path from client to inference servers and back.&nbsp; The team has wide latitude to drive improvements to our expanding SaaS and product surface, uplevel reliability mindsets across Anthropic, and partner with teams internally to build more robust and reliable systems.&nbsp; The breadth and depth of the technical challenges someone joining this team will encounter will be career defining and we are still writing the playbooks. We are at the center of ensuring our customers have a consistently excellent experience.y. Responsibilities Develop appropriate Service Level Objectives for large language model serving and training systems, balancing availability/latency with development velocity. Design and implement monitoring systems including availability, latency and other salient metrics. Assist in the design and implementation of high-availability language model serving infrastructure capable of handling the needs of millions of external customers and high-traffic internal workloads. Develop and manage automated failover and recovery systems for model serving deployments across multiple regions and cloud providers. Lead incident response for critical AI services, ensuring rapid recovery and systematic improvements from each incident Build and maintain cost optimization systems for large-scale AI infrastructure, focusing on accelerator (GPU/TPU/Trainium) utilization and efficiency You may be a good fit if you Have extensive experience with distributed systems observability and monitoring at scale Understand the unique challenges of operating AI infrastructure, including model serving, batch inference, and training pipelines Have proven experience implementing and maintaining SLO/SLA frameworks for business-critical services Are comfortable working with both traditional metrics (latency, availability) and AI-specific metrics (model performance, training convergence) Have experience with chaos engineering and systematic resilience testing Can effectively bridge the gap between ML engineers and infrastructure teams Have excellent communication skills. Strong candidates may also Have experience operating large-scale model training infrastructure or serving infrastructure (&gt;1000 GPUs) Have experience with one or more ML hardware accelerators (GPUs, TPUs, Trainium, e.g.) Understand ML-specific networking optimizations like RDMA and InfiniBand. Have expertise in AI-specific observability tools and frameworks Understand ML model deployment strategies and their reliability implications Have contributed to open-source infrastructure or ML tooling The annual compensation range for this role is listed below.&nbsp; For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.Annual Salary:£255,000&mdash;£325,000 GBPLogistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship:&nbsp;We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.&nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from&nbsp;@anthropic.com&nbsp;email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit&nbsp;anthropic.com/careers&nbsp;directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage:&nbsp;Learn about&nbsp;our policy&nbsp;for using AI in our application process

Senior Software Engineer, AI Reliability Engineering

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.About the Role The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform—from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations. Our engineers are extremely high leverage: we simultaneously drive multiple major revenue streams while optimizing one of Anthropic's most precious resources—compute. As we expand to more cloud platforms, the complexity of managing inference efficiently across providers with different hardware, networking stacks, and operational models grows significantly. We need engineers who can navigate these platform differences, build robust abstractions that work across providers, and make smart infrastructure decisions that keep us cost-effective at massive scale. Your work will increase the scale at which our services operate, accelerate our ability to reliably launch new frontier models and innovative features to customers across all platforms, and ensure our LLMs meet rigorous safety, performance, and security standards. &nbsp; What You'll Do Design and build infrastructure that serves Claude across multiple CSPs, accounting for differences in compute hardware, networking, APIs, and operational models Collaborate with CSP partner engineering teams to resolve operational issues, influence provider roadmaps, and stand up end-to-end serving on new cloud platforms Design and evolve CI/CD automation systems, including validation and deployment pipelines, that reliably ship new model versions to millions of users across cloud platforms without regressions&nbsp; Design interfaces and tooling abstractions across CSPs that enable cost-effective inference management, scale across providers, and reduce per-platform complexity Contribute to capacity planning and autoscaling strategies that dynamically match supply with demand across CSP validation and production workloads Optimize inference cost and performance across providers—designing workload placement and routing systems that direct requests to the most cost-effective accelerator and region Contribute to inference features that must work consistently across all platforms Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads You May Be a Good Fit If You: Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code or container orchestration Have strong interest in inference Thrive in cross-functional collaboration with both internal teams and external partners Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems Are highly autonomous and self-driven, taking ownership of problems end-to-end with a bias toward flexibility and high-impact work Pick up slack, even when it goes outside your job description Strong Candidates May Also Have Experience With Direct experience working with CSP partner teams to scale infrastructure or products across multiple platforms, navigating differences in networking, security, privacy, billing, and managed service offerings A background in building platform-agnostic tooling or abstraction layers that work across cloud providers Hands-on experience with capacity management, cost optimization, or resource planning at scale across heterogeneous environments Strong familiarity with LLM inference optimization, batching, caching, and serving strategies Experience with Machine learning infrastructure including GPUs, TPUs, Trainium, or other AI accelerators Background designing and building CI/CD systems that automate deployment and validation across cloud environments Solid understanding of multi-region deployments, geographic routing, and global traffic management Proficiency in Python or Rust &nbsp;The annual compensation range for this role is listed below.&nbsp; For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.Annual Salary:$300,000&mdash;$485,000 USDLogistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship:&nbsp;We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.&nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from&nbsp;@anthropic.com&nbsp;email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit&nbsp;anthropic.com/careers&nbsp;directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage:&nbsp;Learn about&nbsp;our policy&nbsp;for using AI in our application process

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