The team fosters a collaborative environment and is building a best-in-class program to partner with the business to protect the Firm’s information and computer systems. Millennium is a complex and robust technical environment and securing the Firm from external and internal threats is a top priority.

Responsibilities

• Define and implement security guardrails for Generative AI, LLMs, and Agentic frameworks, ensuring safe enterprise adoption.
• Conduct specialized threat modeling, red teaming, and risk assessments for AI/ML models (e.g., testing for prompt injection, model theft, and data poisoning).
• Lead risk management activities, including application risk assessments, design reviews, and mitigation strategies for IT projects.
• Engage throughout the SDLC to identify vulnerabilities, conduct code reviews/penetration testing, and enforce secure coding standards.
• Evangelize AppSec and AI security best practices through developer education, training materials, and outreach.
• Design robust security architectures and integrate automated security testing (SAST/DAST/SCA) into CI/CD pipelines.
• Partner with Technology, Trading, Legal, and Compliance to create policies and communicate technical risks to non-technical stakeholders.

Qualifications

• Bachelor's degree or higher in Computer Science, Computer Engineering, IT Security or related field.
• 5+ years’ experience working as an Application Security Engineer, Software Engineer, or similar role.
• Deep understanding of AI-specific risks (OWASP Top 10 for LLMs) and experience securing applications utilizing LLMs.
• Experience working with AI models, Agentic frameworks and security risks associated with AI.
• Experience in working with global teams, collaborating on code and presentations.
• Demonstrated work experience in hybrid on-premise and Public Cloud environments (AWS/GCP/Azure)
• Strong understanding of security architectures, secure configuration principles/coding practices, cryptography fundamentals and encryption protocols.
• Experience with common SCM & CI/CD technologies like GitHub, Jenkins, Artifactory, etc. and integrating Security Scanning and Vulnerability Management into the CI/CD Pipelines
• Familiarity with static and dynamic security analysis tools, and SCA/SBOM solutions.
• Hands on experience with Secrets Management & Password Vault technologies such as Delinea Secret Server and/or Hashicorp Vault, etc.
• Strong experience in secure programming in languages such as Python, Java, C++, C#, or similar.
• Familiarity with Infrastructure as Code tools (CloudFormation, Terraform, Ansible, etc.)
• Familiarity with web application security testing tools and methodologies.
• Knowledge of various security frameworks and standards such as ISO 27001, NIST, OWASP, etc.
• Knowledge of Linux, OS internals and containers is a plus.
• Certifications like CISSP, CISM, CompTIA Security+, or CEH are advantageous.

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The successful candidate will have a proven understanding in enterprise security and AI security and will focus on defining and implementing security guardrails for Generative AI, LLMs, and Agentic frameworks, ensuring safe enterprise adoption.

Key responsibilities include:

• Defining and implementing security guardrails for Generative AI, LLMs, and Agentic frameworks
• Conducting specialized threat modeling, red teaming, and risk assessments for AI/ML models
• Leading risk management activities, including application risk assessments, design reviews, and mitigation strategies for IT projects
• Engaging throughout the SDLC to identify vulnerabilities, conduct code reviews/penetration testing, and enforce secure coding standards
• Evangelizing AppSec and AI security best practices through developer education, training materials, and outreach

Qualifications include:

• Bachelor's degree or higher in Computer Science, Computer Engineering, IT Security or related field
• 5+ years' experience working as an Application Security Engineer, Software Engineer, or similar role
• Deep understanding of AI-specific risks (OWASP Top 10 for LLMs) and experience securing applications utilizing LLMs
• Experience working with AI models, Agentic frameworks and security risks associated with AI
• Experience in working with global teams, collaborating on code and presentations

Preferred qualifications include:

• Demonstrated work experience in hybrid on-premise and Public Cloud environments (AWS/GCP/Azure)
• Strong understanding of security architectures, secure configuration principles/coding practices, cryptography fundamentals and encryption protocols
• Experience with common SCM & CI/CD technologies like GitHub, Jenkins, Artifactory, etc. and integrating Security Scanning and Vulnerability Management into the CI/CD Pipelines
• Familiarity with static and dynamic security analysis tools, and SCA/SBOM solutions
• Hands on experience with Secrets Management & Password Vault technologies such as Delinea Secret Server and/or Hashicorp Vault, etc.
• Strong experience in secure programming in languages such as Python, Java, C++, C#, or similar
• Familiarity with Infrastructure as Code tools (CloudFormation, Terraform, Ansible, etc.)
• Familiarity with web application security testing tools and methodologies
• Knowledge of various security frameworks and standards such as ISO 27001, NIST, OWASP, etc.
• Knowledge of Linux, OS internals and containers is a plus
• Certifications like CISSP, CISM, CompTIA Security+, or CEH are advantageous

We offer a competitive salary and benefits package, as well as opportunities for professional growth and development.

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Key responsibilities include designing, running, and analyzing scientific experiments to advance our understanding of large language models. Additionally, you will optimize and scale our training infrastructure to improve efficiency and reliability, and develop and improve dev tooling to enhance team productivity.

As a Research Engineer, you will contribute to the entire stack, from low-level optimizations to high-level model design. You will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems.

The ideal candidate will have an advanced degree in Computer Science, Machine Learning, or a related field, and strong software engineering skills with a proven track record of building complex systems. You should be familiar with Python and experience with deep learning frameworks, particularly PyTorch. Additionally, you should have expertise in large-scale machine learning, particularly in the context of language models.

You will thrive in this role if you have significant software engineering experience, are results-oriented with a bias towards flexibility and impact, willing to take on tasks outside your job description to support the team, enjoy pair programming and collaborative work, and are eager to learn more about machine learning research.

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Responsibilities:

• Conduct research into the science of converting compute into intelligence
• Independently lead small research projects while collaborating with team members on larger initiatives
• Design, run, and analyze scientific experiments to advance our understanding of large language models
• Optimize training infrastructure to improve efficiency and reliability
• Develop dev tooling to enhance team productivity

You may be a good fit if you:

• Have significant software engineering experience and a proven track record of building complex systems
• Hold an advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field
• Are proficient in Python and experienced with deep learning frameworks
• Are results-oriented with a bias towards flexibility and impact
• Enjoy pair programming and collaborative work, and are willing to take on tasks outside your job description to support the team
• View research and engineering as two sides of the same coin, seeking to understand all aspects of the research program to maximize impact
• Care about the societal impacts of your work and have ambitious goals for AI safety and general progress

Strong candidates may have:

• Experience with JAX
• Experience with reinforcement learning
• Experience working on high-performance, large-scale ML systems
• Familiarity with accelerators, Kubernetes, and OS internals
• Experience with language modeling using transformer architectures
• Background in large-scale ETL processes
• Experience with distributed training at scale (thousands of accelerators)

Strong candidates need not have:

• Experience in all of the above areas , we value breadth of interest and willingness to learn over checking every box
• Prior work specifically on language models or transformers; strong engineering fundamentals and ML knowledge transfer well
• An advanced degree , exceptional engineers with strong research instincts are equally encouraged to apply

The annual compensation range for this role is £260,000-£630,000 GBP.

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You'll be working on large-scale ML systems from the ground up, making safe, steerable, trustworthy systems. You'll be excited to write code when you understand the research context and more broadly why it's important.

Strong candidates may also have experience with high performance, large-scale ML systems, GPUs, Kubernetes, Pytorch, or OS internals, language modeling with transformers, reinforcement learning, and large-scale ETL.

Representative projects may include optimizing the throughput of a new attention mechanism, comparing the compute efficiency of two Transformer variants, making a Wikipedia dataset in a format models can easily consume, scaling a distributed training job to thousands of GPUs, writing a design doc for fault tolerance strategies, and creating an interactive visualization of attention between tokens in a language model.

The annual compensation range for this role is $350,000-$500,000 USD.

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As an Engineering Manager on Anthropic's performance and scaling teams, you will be responsible for ensuring the team is identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems.

Responsibilities:

• Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems
• Become familiar with the team's technical stack enough to make targeted contributions as an individual contributor
• Manage day-to-day execution of the team's work
• Prioritize the team's work and manage projects in a highly dynamic, fast-paced environment
• Coach and support your reports in understanding, and pursuing, their professional growth
• Maintain a deep understanding of the team's technical work and its implications for AI safety

Requirements:

• 1+ years of management experience in a technical environment, particularly performance or distributed systems
• Background in machine learning, AI, or a similar related technical field
• Deeply interested in the potential transformative effects of advanced AI systems and committed to ensuring their safe development
• Excel at building strong relationships with stakeholders at all levels
• Quick learner, capable of understanding and contributing to discussions on complex technical topics
• Experience managing teams through periods of rapid growth and change

Nice to have:

• High performance, large-scale ML systems
• GPU/Accelerator programming
• ML framework internals
• OS internals
• Language modeling with transformers

Compensation:

The annual compensation range for this role is $425,000-$560,000 USD.

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You will work closely with our team of researchers, engineers, and policy experts to build beneficial AI systems. Your contributions will have a direct impact on the development of our AI technology and its applications.

We are looking for a highly motivated and experienced engineer who is passionate about solving complex systems problems and has a strong background in software engineering or machine learning. If you are excited about the opportunity to work on cutting-edge AI technology and make a meaningful contribution to the field, we encourage you to apply.

Responsibilities:

• Identify and solve novel systems problems that arise when running machine learning algorithms at scale
• Develop systems that optimize the throughput and robustness of our largest distributed systems
• Collaborate with our team of researchers, engineers, and policy experts to build beneficial AI systems
• Contribute to the development of our AI technology and its applications

Requirements:

• Significant software engineering or machine learning experience, particularly at supercomputing scale
• Results-oriented, with a bias towards flexibility and impact
• Ability to pick up slack, even if it goes outside your job description
• Enjoy pair programming
• Want to learn more about machine learning research
• Care about the societal impacts of your work

Preferred qualifications:

• Experience with high-performance, large-scale ML systems
• GPU/Accelerator programming
• ML framework internals
• OS internals
• Language modeling with transformers

Benefits:

• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours
• Lovely office space in which to collaborate with colleagues

Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process

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As an Engineering Manager on Anthropic's performance and scaling teams, you will be responsible for ensuring your team identifies and removes bottlenecks, builds robust and durable solutions, and maximizes the efficiency of our systems.

Responsibilities:

• Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems
• Become familiar with the team's technical stack enough to make targeted contributions as an individual contributor
• Manage day-to-day execution of the team's work
• Prioritize the team's work and manage projects in a highly dynamic, fast-paced environment
• Coach and support your reports in understanding, and pursuing, their professional growth
• Maintain a deep understanding of the team's technical work and its implications for AI safety

You may be a good fit if you:

• Have 1+ years of management experience in a technical environment, particularly performance or distributed systems
• Have a background in machine learning, AI, or a similar related technical field
• Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development
• Excel at building strong relationships with stakeholders at all levels
• Are a quick learner, capable of understanding and contributing to discussions on complex technical topics
• Have experience managing teams through periods of rapid growth and change

Strong candidates may also have experience with:

• High-performance, large-scale ML systems
• GPU/Accelerator programming
• ML framework internals
• OS internals
• Language modeling with transformers

The annual compensation range for this role is $500,000-$850,000 USD.

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Job Description

We are a technology organisation operating high performance, large scale Linux production environments that support critical platforms and engineering teams. Our focus is on operational excellence, service reliability, automation, and continuous improvement. We run 24x7 operations and partner closely with platform, network, security, and engineering teams to deliver stable, secure, and scalable infrastructure.

Responsibilities

• Leading and managing a 24x7 L1 Linux Engineering / SRE team operating in rotational shifts
• Owning hiring, onboarding, performance management, coaching, and career development for L1 engineers
• Owning L1 production support operations for Linux systems in a 24x7 environment
• Acting as the first leadership escalation point during major production incidents
• Ensuring adherence to SLAs, OLAs, and operational KPIs such as availability and MTTR
• Providing technical oversight across Linux OS, bare metal and virtualized platforms, and monitoring/logging systems
• Driving automation adoption using Ansible, Bash, and Python to reduce manual toil
• Defining and maintaining SOPs, runbooks, escalation procedures, and documentation
• Partnering with platform, network, security, and engineering teams to improve system reliability and resilience

Impact

• Ensuring stable, reliable, and efficient 24x7 L1 Linux/SRE operations
• Reducing incident recurrence and improving incident response and resolution times
• Building a skilled, motivated, and well-governed L1 engineering team
• Improving operational maturity through automation, standardization, and documentation
• Enabling engineering and R&D teams through predictable and resilient platform operations

Requirements

• 10–14+ years of experience in IT Infrastructure, Linux Operations, or SRE
• 4–6+ years of people management experience, preferably managing 24x7 support teams
• Strong hands-on background in Linux system administration and production support
• Experience with incident management, on-call models, and rotational shifts
• Advanced knowledge of Linux OS internals
• Experience with virtualization platforms (VMware, KVM, OpenStack, oVirt)
• Knowledge of monitoring and logging tools (e.g., Nagios, ELK)
• Experience with automation and configuration management (Ansible)
• Scripting skills in Bash and/or Python

Who You Are

• A strong people leader with excellent coaching and decision-making skills
• Calm and effective under high-pressure production scenarios
• Highly structured and data-driven in driving operational excellence
• An effective communicator and stakeholder partner
• Passionate about reliability engineering, automation, and continuous improvement

Rewards and Benefits

• Opportunity to lead mission-critical, large-scale Linux and SRE operations
• High visibility role with exposure to senior leadership and engineering stakeholders
• Ability to shape operational strategy, automation, and reliability practices
• Strong focus on career growth, learning, and leadership development

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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's performance and scaling teams focus on making the most efficient and impactful use of our compute resources, be it inference or training. As an Engineering Manager on these teams you will be responsible for ensuring you and your team are identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems. You also will help bring clarity, focus, and context to your teams in a fast paced, dynamic environment.

Responsibilities:

• Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems
• Become familiar with the team’s technical stack enough to make targeted contributions as an individual contributor
• Manage day-to-day execution of the team's work
• Prioritize the team’s work and manage projects in a highly dynamic, fast paced environment
• Coach and support your reports in understanding, and pursuing, their professional growth
• Maintain a deep understanding of the team's technical work and its implications for AI safety

You may be a good fit if you:

• Have 1+ years of management experience in a technical environment, particularly performance or distributed systems
• Have a background in machine learning, AI, or a similar related technical field
• Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development
• Excel at building strong relationships with stakeholders at all levels
• Are a quick learner, capable of understanding and contributing to discussions on complex technical topics
• Have experience managing teams through periods of rapid growth and change
• Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you’ll need to understand (at a high level of abstraction) to be effective

Strong candidates may also have experience with:

• High performance, large-scale ML systems
• GPU/Accelerator programming
• ML framework internals
• OS internals
• Language modeling with transformers

Logistics

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:

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. 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.

Your safety matters to us.

To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com 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 anthropic.com/careers 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 & 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 paid time off, and a comprehensive benefits package.

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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 a Research Engineer/Scientist to join the Science of Scaling team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. You'll contribute across the entire stack, from low-level optimizations to high-level algorithm and experimental design, balancing research goals with practical engineering constraints.

Responsibilities:

• Conduct research into the science of converting compute into intelligence
• Independently lead small research projects while collaborating with team members on larger initiatives
• Design, run, and analyse scientific experiments to advance our understanding of large language models
• Optimise training infrastructure to improve efficiency and reliability
• Develop dev tooling to enhance team productivity

You may be a good fit if you:

• Have significant software engineering experience and a proven track record of building complex systems
• Hold an advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field
• Are proficient in Python and experienced with deep learning frameworks
• Are results-oriented with a bias towards flexibility and impact
• Enjoy pair programming and collaborative work, and are willing to take on tasks outside your job description to support the team
• View research and engineering as two sides of the same coin, seeking to understand all aspects of the research program to maximise impact
• Care about the societal impacts of your work and have ambitious goals for AI safety and general progress

Strong candidates may have:

• Experience with JAX
• Experience with reinforcement learning
• Experience working on high-performance, large-scale ML systems
• Familiarity with accelerators, Kubernetes, and OS internals
• Experience with language modeling using transformer architectures
• Background in large-scale ETL processes
• Experience with distributed training at scale (thousands of accelerators)

Strong candidates need not have:

• Experience in all of the above areas — we value breadth of interest and willingness to learn over checking every box
• Prior work specifically on language models or transformers; strong engineering fundamentals and ML knowledge transfer well
• An advanced degree — exceptional engineers with strong research instincts are equally encouraged to apply

Logistics

• 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: 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. 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.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com 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 anthropic.com/careers 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

XML job scraping automation by YubHub

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.

Key Responsibilities:

• Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development

• Independently lead small research projects while collaborating with team members on larger initiatives

• Design, run, and analyse scientific experiments to advance our understanding of large language models

• Optimise and scale our training infrastructure to improve efficiency and reliability

• Develop and improve dev tooling to enhance team productivity

• Contribute to the entire stack, from low-level optimisations to high-level model design

Qualifications:

• Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field

• Strong software engineering skills with a proven track record of building complex systems

• Expertise in Python and experience with deep learning frameworks (PyTorch preferred)

• Familiarity with large-scale machine learning, particularly in the context of language models

• Ability to balance research goals with practical engineering constraints

• Strong problem-solving skills and a results-oriented mindset

• Excellent communication skills and ability to work in a collaborative environment

• Care about the societal impacts of your work

Preferred Experience:

• Work on high-performance, large-scale ML systems

• Familiarity with GPUs, Kubernetes, and OS internals

• Experience with language modelling using transformer architectures

• Knowledge of reinforcement learning techniques

• Background in large-scale ETL processes

You'll thrive in this role if you:

• Have significant software engineering experience

• Are results-oriented with a bias towards flexibility and impact

• Willingly take on tasks outside your job description to support the team

• Enjoy pair programming and collaborative work

• Are eager to learn more about machine learning research

• Are enthusiastic to work at an organisation that functions as a single, cohesive team pursuing large-scale AI research projects

• Are working to align state of the art models with human values and preferences, understand and interpret deep neural networks, or develop new models to support these areas of research

• View research and engineering as two sides of the same coin, and seek to understand all aspects of our research program as well as possible, to maximise the impact of your insights

• Have ambitious goals for AI safety and general progress in the next few years, and you’re working to create the best outcomes over the long-term.

Sample Projects:

• Optimising the throughput of novel attention mechanisms

• Comparing compute efficiency of different Transformer variants

• Preparing large-scale datasets for efficient model consumption

• Scaling distributed training jobs to thousands of GPUs

• Designing fault tolerance strategies for our training infrastructure

• Creating interactive visualisations of model internals, such as attention patterns

Benefits:

At Anthropic, we are committed to fostering a diverse and inclusive workplace. We strongly encourage applications from candidates of all backgrounds, including those from underrepresented groups in tech.

Logistics:

• 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: 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. 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.

• Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from https://job-boards.greenhouse.io.

XML job scraping automation by YubHub

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.

Key Responsibilities:

• Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development
• Independently lead small research projects while collaborating with team members on larger initiatives
• Design, run, and analyse scientific experiments to advance our understanding of large language models
• Optimise and scale our training infrastructure to improve efficiency and reliability
• Develop and improve dev tooling to enhance team productivity
• Contribute to the entire stack, from low-level optimisations to high-level model design

Qualifications:

• Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field
• Strong software engineering skills with a proven track record of building complex systems
• Expertise in Python and experience with deep learning frameworks (PyTorch preferred)
• Familiarity with large-scale machine learning, particularly in the context of language models
• Ability to balance research goals with practical engineering constraints
• Strong problem-solving skills and a results-oriented mindset
• Excellent communication skills and ability to work in a collaborative environment
• Care about the societal impacts of your work

Preferred Experience:

• Work on high-performance, large-scale ML systems
• Familiarity with GPUs, Kubernetes, and OS internals
• Experience with language modelling using transformer architectures
• Knowledge of reinforcement learning techniques
• Background in large-scale ETL processes

You'll thrive in this role if you:

• Have significant software engineering experience
• Are results-oriented with a bias towards flexibility and impact
• Willingly take on tasks outside your job description to support the team
• Enjoy pair programming and collaborative work
• Are eager to learn more about machine learning research
• Are enthusiastic to work at an organisation that functions as a single, cohesive team pursuing large-scale AI research projects
• Are working to align state of the art models with human values and preferences, understand and interpret deep neural networks, or develop new models to support these areas of research
• View research and engineering as two sides of the same coin, and seek to understand all aspects of our research program as well as possible, to maximise the impact of your insights
• Have ambitious goals for AI safety and general progress in the next few years, and you’re working to create the best outcomes over the long-term.

Sample Projects:

• Optimising the throughput of novel attention mechanisms
• Comparing compute efficiency of different Transformer variants
• Preparing large-scale datasets for efficient model consumption
• Scaling distributed training jobs to thousands of GPUs
• Designing fault tolerance strategies for our training infrastructure
• Creating interactive visualisations of model internals, such as attention patterns

At Anthropic, we are committed to fostering a diverse and inclusive workplace. We strongly encourage applications from candidates of all backgrounds, including those from underrepresented groups in tech.

If you're excited about pushing the boundaries of AI while prioritising safety and ethics, we want to hear from you!

The annual compensation range for this role is listed below.

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:

$350,000 - $850,000USD

XML job scraping automation by YubHub

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.

You may be a good fit if you:

• Have significant software engineering experience
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Want to learn more about machine learning research
• Care about the societal impacts of your work

Strong candidates may also have experience with:

• High performance, large-scale ML systems
• GPUs, Kubernetes, Pytorch, or OS internals
• Language modeling with transformers
• Reinforcement learning
• Large-scale ETL

Representative projects:

• Optimizing the throughput of a new attention mechanism
• Comparing the compute efficiency of two Transformer variants
• Making a Wikipedia dataset in a format models can easily consume
• Scaling a distributed training job to thousands of GPUs
• Writing a design doc for fault tolerance strategies
• Creating an interactive visualization of attention between tokens in a language model

Annual compensation range for this role is listed below.

Annual Salary:

$350,000 - $500,000USD

Logistics

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: 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.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com 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 anthropic.com/careers 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 & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in California, USA.

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Running machine learning (ML) algorithms at our scale often requires solving novel systems problems. As a Performance Engineer, you'll be responsible for identifying these problems, and then developing systems that optimize the throughput and robustness of our largest distributed systems. Strong candidates here will have a track record of solving large-scale systems problems and will be excited to grow to become an expert in ML also.

You may be a good fit if you:

• Have significant software engineering or machine learning experience, particularly at supercomputing scale
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Want to learn more about machine learning research
• Care about the societal impacts of your work

Strong candidates may also have experience with:

• High performance, large-scale ML systems
• GPU/Accelerator programming
• ML framework internals
• OS internals
• Language modeling with transformers

Representative projects:

• Implement low-latency high-throughput sampling for large language models
• Implement GPU kernels to adapt our models to low-precision inference
• Write a custom load-balancing algorithm to optimize serving efficiency
• Build quantitative models of system performance
• Design and implement a fault-tolerant distributed system running with a complex network topology
• Debug kernel-level network latency spikes in a containerized environment

Deadline to apply:

None. Applications will be reviewed on a rolling basis.

Logistics

• 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: 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. 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.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com 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 anthropic.com/careers 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 & 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:

Learn about our policy for using AI in our application process

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Anthropic's performance and scaling teams focus on making the most efficient and impactful use of our compute resources, be it inference or training. As an Engineering Manager on these teams, you will be responsible for ensuring you and your team are identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems. You also will help bring clarity, focus, and context to your teams in a fast-paced, dynamic environment.

Responsibilities:

• Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems
• Become familiar with the team's technical stack enough to make targeted contributions as an individual contributor
• Manage day-to-day execution of the team's work
• Prioritize the team's work and manage projects in a highly dynamic, fast-paced environment
• Coach and support your reports in understanding, and pursuing, their professional growth
• Maintain a deep understanding of the team's technical work and its implications for AI safety

You may be a good fit if you:

• Have 1+ years of management experience in a technical environment, particularly performance or distributed systems
• Have a background in machine learning, AI, or a similar related technical field
• Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development
• Excel at building strong relationships with stakeholders at all levels
• Are a quick learner, capable of understanding and contributing to discussions on complex technical topics
• Have experience managing teams through periods of rapid growth and change
• Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you'll need to understand (at a high level of abstraction) to be effective

Strong candidates may also have experience with:

• High performance, large-scale ML systems
• GPU/Accelerator programming
• ML framework internals
• OS internals
• Language modeling with transformers

Logistics

• 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: 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.

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.

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 policies, and a dynamic and inclusive work environment.

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About the Team

OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI.

About the Role

We’re seeking a Networking Operating System Firmware Engineer to help bootstrap and scale the switching layer of our AI supercomputers. In this role, you’ll build and maintain custom SONiC NOS images from scratch, working across the Linux kernel, switch ASIC SAI/SDKs, platform drivers, control-plane services, and orchestration layers.

You will validate, configure, and optimize switch platforms used across our high-bandwidth cluster fabric, ensuring performance, reliability, availability, and seamless integration with fleet automation. You’ll collaborate with hardware and systems teams and guide vendors to meet stringent technical expectations.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Design, develop, and maintain custom SONiC NOS images for large-scale bleeding-edge AI fabrics.

• Integrate and configure Linux kernel components, device drivers, switch ASIC SDKs, and SAI layers.

• Bring up new switch platforms (thermal/fan control, power monitoring, transceiver management, watchdogs, OSFP CMIS, LEDs, CPLDs, etc.).

• Extend and customize SONiC services for routing, telemetry, control-plane state, and distributed automation.

• Work with hardware teams to validate ASIC configurations, link bring-up, SerDes tuning, buffer profiles, and performance baselines.

• Evaluate switch silicon SDK releases, track vendor deliverables, and define platform requirements with vendors and ASIC partners.

• Debug complex issues spanning kernel, platform drivers, SONiC dockers, routing agents, orchestration services, hardware signals, and network topology.

• Integrate switches into fleet-wide monitoring, remote diagnostics, telemetry pipelines, and automated lifecycle workflows.

• Develop robust CI/build pipelines for reproducible NOS builds and controlled rollout across the fleet.

• Support factory bring-up and qualification all the way through mass deployment.

• Collaborate, architect, implement, and deploy novel networking protocols and technologies to achieve maximum performance and reliability at AI factory scale.

You might thrive in this role if you:

• Proven experience working with SONiC or comparable NOS stacks (FBOSS, Cumulus Linux, Arista EOS, Junos PFE-level integration, etc.).

• Experience with updating OpenConfig gNMI interfaces and YANG data models.

• Strong background in Linux kernel, network device drivers, and low-level OS internals.

• Experience integrating Broadcom / Marvell / NVIDIA / Intel ASIC SDKs and SAI implementations.

• Proficiency in C, C++ and Python; familiarity with Rust/Go is a plus.

• Deep understanding of L2/L3 forwarding, ECMP, RoCE, BGP, QoS, PFC, buffer tuning, and telemetry.

• Hands-on experience with hardware platform bring-up and board-level debugging.

• Familiarity with CI/CD pipelines, distributed config/state management, and large-scale automation.

• Strong cross-functional problem solving in high-performance, distributed environments.

• Ability to lead teams to deliver a project end to end.

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Location

San Francisco

Employment Type

Full time

Department

Consumer Products

Compensation

• $293K – $325K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

Location: San Francisco, CA (Hybrid: 4 days onsite/week). Relocation assistance available.

About the Team:

We build foundational platform software that enables reliable, secure, and performant products. The team works across system layers and partners closely with adjacent engineering groups to deliver robust capabilities from concept through launch.

About the Role:

We’re seeking a Systems Software Engineer to design, implement, and debug core platform components and the pipelines that build and update system images. You’ll work across operating system layers, focusing on performance, security, and deep system debugging to ship production‑grade systems.

In this role, you will:

• Design, implement, and debug system‑level components and services across kernel and user space.

• Configure and maintain OS platform services (init, services, networking, security policies) and related tooling.

• Build and operate image and update pipelines, ensuring reliability, reproducibility, and rollback safety.

• Instrument and analyze performance using profiling and tracing; optimize CPU, memory, I/O, and power usage.

• Own platform observability and reliability: logging, crash capture, watchdogs, and diagnostics.

• Collaborate with cross‑functional teams to define interfaces and deliver end‑to‑end features.

• Establish strong engineering practices: code review, CI, reproducible builds, and release management.

• Partner with external suppliers to support builds and deployments.

You might thrive in this role if you:

• Have shipped production systems software on modern operating systems.

• Are proficient in C/C++ and a scripting language, and comfortable with OS internals (concurrency, memory management, filesystems, networking, power management).

• Bring strong systems debugging skills using debuggers, tracers, profilers, and logs across kernel/user‑space boundaries.

• Understand configuration of platform services and interfaces, and can translate requirements into stable, well‑documented APIs.

• Are fluent in user‑space foundations (service management, IPC, networking, packaging, automation).

• Have experience building platform images and designing update mechanisms for reliability and security.

Preferred Qualifications:

• Exposure to platform security (secure boot, sandboxing, mandatory access controls, attestation).

• Experience with graphics/media, hardware acceleration, or high‑throughput data paths.

• Familiarity with connectivity stacks and network configuration.

• Observability and diagnostics in distributed or resource‑constrained environments.

• Work on open‑source platforms or contributions to systems projects.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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