Apply using this link. We are accepting applications on a rolling basis for the next cohort of Anthropic Fellows, which is expected to start in late September. In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the September start date doesn't work for you.

This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting.

Anthropic Fellows Program overview

The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience.

Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers.

We run multiple cohorts of Fellows each year and review applications on a rolling basis. This application is for cohorts starting in July 2026 and beyond.

What to expect

• 4 months of full-time research 
• Direct mentorship from Anthropic researchers 
• Access to a shared workspace (in either Berkeley, California or London, UK)
• Connection to the broader AI safety and security research community
• Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country)
• Funding for compute (~$15k/month) and other research expenses

Interview process

The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion. 

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. 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.

Compensation

The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension).

Fellows workstreams

Due to the success of the Anthropic Fellows for AI Safety Research program, we are now expanding it across teams at Anthropic. We expect there to be significant overlap in the types of skills and responsibilities across the roles and will by default consider candidates for all the workstreams.

Some of the workstreams may include unique assessment steps; we therefore ask you for workstream preferences in the application. You can see an overview of the current workstreams below:

1. AI Safety Fellows
2. AI Security Fellows
3. ML Systems & Performance Fellows
4. Reinforcement Learning Fellows
5. Economics & Societal Impacts Fellows

This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting.

Across the workstreams, you may be a good fit if you:

• Are motivated by making sure AI is safe and beneficial for society as a whole
• Are excited to transition into empirical AI research and would be interested in a full-time role at Anthropic
• Have a strong technical background in computer science, mathematics, or physics
• Thrive in fast-paced, collaborative environments
• Can implement ideas quickly and communicate clearly

Strong candidates may also have:

• Strong background in a discipline relevant to a specific Fellows workstream (e.g. economics, social sciences, or cybersecurity)
• Experience in areas of research or engineering related to their workstream

Candidates must be:

• Fluent in Python programming
• Available to work full-time on the Fellows program

The Anthropic Institute Fellows (Economics & Policy)

Mentors, research areas, & past projects

Fellows will undergo a project selection & mentor matching process. Potential research areas and mentors include:

• Economics
  • Maxim Massenkoff
  • Peter McCrory
• Policy, Security, and Society
  
  • Jack Clark
  • Marina Favaro
  • Jim Baker

Projects in this workstream may include:

• Designing and conducting empirical research on AI's economic effects, drawing on external data sources
• Developing new methodological approaches for studying AI's impact on labor markets, the future of work, and society
• Analysing the offense–defense balance for AI-enabled cyber and bio capabilities as models scale
• Measuring the extent to which model performance increases with custom harnesses?
• Identifying market driven mechanisms that could improve societal resilience to anticipated threats from AI systems?
• Identifying which metrics relating to AI R&D could service as early warning signals for recursive self-improvement

For past project examples, see:

• How AI Impacts Skill Formation: Judy Shen and Alex Tamkin
• Stress-Testing Model Specs Reveals Character Differences among Language Models: Jifan Zhang, Henry Sleight, Andi Peng, John Schulman, and Esin Durmus

Unique candidate criteria

You might be a particularly great fit for this workstream if you:

• Have an interest in economics or policy research; prior experience in this area is a plus but not required
• Are adaptable and collaborative, able to take direction and contribute to team priorities rather than needing to pursue a predetermined research agenda
• Are skilled at writing up and communicating your results, even when they're null or unexpected
• Are passionate about translating research insights into actionable recommendations for improving AI systems and informing policy

Logistics

Logistics Requirements: To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program.

Workspace Locations: We have designated shared workspaces in London and Berkeley where fellows will work from and mentors will visit. We are also open to remote fellows in the UK, US, or Canada. We will ask you about your availability to work from Berkeley or London (full- or part-time) during the program.

Visa Sponsorship: We are not currently able to sponsor visas for fellows. To participate in the Fellows program, you need to have or independently obtain full-time work authorization in the UK, the US, or Canada.

Program Duration: The program runs for 4 months, full-time. If you can't commit to the full duration, please still apply and note your constraints in the application. We review these requests on a case-by-case basis.

Please note: We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organizations.

Applications and interviews are managed by Constellation, our recruiting partner. Clicking "Apply here" will take you to their portal, and updates will come from a Constellation address. Constellation also runs the Berkeley workspace and provides program support for fellows working on AI safety and security; fellows on capabilities-focused projects are supported directly by Anthropic. All applicants currently use the same application portal but we are working to separate applications for safety/security and capabilities focused projects in future rounds.

Apply here

The below are Anthropic's policies for full time roles. These do NOT apply to the Fellows Program.

Apply using this link. We are accepting applications on a rolling basis for the next cohort of Anthropic Fellows, which is expected to start in late September. In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the September start date doesn't work for you.

This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting.

Anthropic Fellows Program overview

The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience.

Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers.

We run multiple cohorts of Fellows each year and review applications on a rolling basis. This application is for cohorts starting in July 2026 and beyond.

What to expect

• 4 months of full-time research 
• Direct mentorship from Anthropic researchers 
• Access to a shared workspace (in either Berkeley, California or London, UK)
• Connection to the broader AI safety and security research community
• Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country)
• Funding for compute (~$15k/month) and other research expenses

Interview process

The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion. 

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. 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.

Compensation

The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension).

Fellows workstreams

Due to the success of the Anthropic Fellows for AI Safety Research program, we are now expanding it across teams at Anthropic. We expect there to be significant overlap in the types of skills and responsibilities across the roles and will by default consider candidates for all the workstreams.

Some of the workstreams may include unique assessment steps; we therefore ask you for workstream preferences in the application. You can see an overview of the current workstreams below:

1. AI Safety Fellows
2. AI Security Fellows
3. ML Systems & Performance Fellows
4. Reinforcement Learning Fellows
5. Economics & Societal Impacts Fellows

This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting.

Across the workstreams, you may be a good fit if you:

• Are motivated by making sure AI is safe and beneficial for society as a whole
• Are excited to transition into empirical AI research and would be interested in a full-time role at Anthropic
• Have a strong technical background in computer science, mathematics, or physics
• Thrive in fast-paced, collaborative environments
• Can implement ideas quickly and communicate clearly

Strong candidates may also have:

• Strong background in a discipline relevant to a specific Fellows workstream (e.g. economics, social sciences, or cybersecurity)
• Experience in areas of research or engineering related to their workstream

Candidates must be:

• Fluent in Python programming
• Available to work full-time on the Fellows program

Reinforcement Learning Fellows

Mentors, research areas, & past projects

Fellows will undergo a project selection & mentor matching process. Potential research areas and mentors include:

• Ruhua Jiang
• Kaidi Cao
• Sunny Duan
• David Brandfonbrener
• Colt Steele
• Dino Distefano
• Will Williams

Projects in this workstream may include:

• Building model-based tools to better understand AI training data and improve training data quality
• A research project to better understand generalization
• Creating RL environments to improve Claude models at capabilities that are within your domain of expertise
• Building RL environments for safety-related tasks
• Conducting research and implementing solutions in areas such as RL algorithms

Unique candidate criteria

You might be a particularly great fit for this workstream if you:

• Have strong software engineering skills with experience building complex ML systems
• Can balance research exploration with engineering rigor and operational reliability
• Enjoy collaborating across research and engineering disciplines
• Are comfortable working with large-scale distributed systems and high-performance computing
• Have experience with training, fine-tuning, or evaluating large language models
• Are adept at analyzing and debugging model training processes

Logistics

Logistics Requirements: To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program.

Workspace Locations: We have designated shared workspaces in London and Berkeley where fellows will work from and mentors will visit. We are also open to remote fellows in the UK, US, or Canada. We will ask you about your availability to work from Berkeley or London (full- or part-time) during the program.

Visa Sponsorship: We are not currently able to sponsor visas for fellows. To participate in the Fellows program, you need to have or independently obtain full-time work authorization in the UK, the US, or Canada.

Program Duration: The program runs for 4 months, full-time. If you can't commit to the full duration, please still apply and note your constraints in the application. We review these requests on a case-by-case basis.

Please note: We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organizations.

Applications and interviews are managed by Constellation, our recruiting partner. Clicking "Apply here" will take you to their portal, and updates will come from a Constellation address. Constellation also runs the Berkeley workspace and provides program support for fellows working on AI safety and security; fellows on capabilities-focused projects are supported directly by Anthropic. All applicants currently use the same application portal but we are working to separate applications for safety/security and capabilities focused projects in future rounds.

Apply here

The below are Anthropic's policies for full time roles. These do NOT apply to the Fellows Program.

Apply using this link. We are accepting applications on a rolling basis for the next cohort of Anthropic Fellows, which is expected to start in late September. In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the September start date doesn't work for you.

This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting.

Anthropic Fellows Program overview

The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience.

Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers.

We run multiple cohorts of Fellows each year and review applications on a rolling basis. This application is for cohorts starting in July 2026 and beyond.

What to expect

• 4 months of full-time research 
• Direct mentorship from Anthropic researchers 
• Access to a shared workspace (in either Berkeley, California or London, UK)
• Connection to the broader AI safety and security research community
• Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country)
• Funding for compute (~$15k/month) and other research expenses

Interview process

The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion. 

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. 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.

Compensation

The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension).

Fellows workstreams

Due to the success of the Anthropic Fellows for AI Safety Research program, we are now expanding it across teams at Anthropic. We expect there to be significant overlap in the types of skills and responsibilities across the roles and will by default consider candidates for all the workstreams.

Some of the workstreams may include unique assessment steps; we therefore ask you for workstream preferences in the application. You can see an overview of the current workstreams below:

1. AI Safety Fellows
2. AI Security Fellows
3. ML Systems & Performance Fellows
4. Reinforcement Learning Fellows
5. Economics & Societal Impacts Fellows

This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting.

Across the workstreams, you may be a good fit if you:

• Are motivated by making sure AI is safe and beneficial for society as a whole
• Are excited to transition into empirical AI research and would be interested in a full-time role at Anthropic
• Have a strong technical background in computer science, mathematics, or physics
• Thrive in fast-paced, collaborative environments
• Can implement ideas quickly and communicate clearly

Strong candidates may also have:

• Strong background in a discipline relevant to a specific Fellows workstream (e.g. economics, social sciences, or cybersecurity)
• Experience in areas of research or engineering related to their workstream

Candidates must be:

• Fluent in Python programming
• Available to work full-time on the Fellows program

ML Systems & Performance Fellows

Mentors, research areas, & past projects

Fellows will undergo a project selection & mentor matching process. Potential mentors include:

• Alwin Peng
• Zygi Straznickas

Note: You may research mentors' prior work, but all applications must go through the official form, not the mentors.

For a past example of an engineering-heavy project, see:

• AI agents find $4.6M in blockchain smart contract exploits

Projects in this workstream may include:

• Building a CPU simulator for accelerator workloads
• Adding backends for different accelerators on an open source project
• Building on demand infrastructure for other infrastructure heavy fellows projects 
• Building complex synthetic data or environment pipelines

Unique candidate criteria

You might be a particularly great fit for this workstream if you:

• Have strong software engineering skills with experience building complex ML systems
• Can balance research exploration with engineering rigor and operational reliability
• Enjoy collaborating across research and engineering disciplines
• Are comfortable working with large-scale distributed systems and high-performance computing (e.g. in trading)
• Have experience with training, fine-tuning, or evaluating large language models
• Are adept at analyzing and debugging model training processes

Logistics

Logistics Requirements: To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program.

Workspace Locations: We have designated shared workspaces in London and Berkeley where fellows will work from and mentors will visit. We are also open to remote fellows in the UK, US, or Canada. We will ask you about your availability to work from Berkeley or London (full- or part-time) during the program.

Visa Sponsorship: We are not currently able to sponsor visas for fellows. To participate in the Fellows program, you need to have or independently obtain full-time work authorization in the UK, the US, or Canada.

Program Duration: The program runs for 4 months, full-time. If you can't commit to the full duration, please still apply and note your constraints in the application. We review these requests on a case-by-case basis.

Please note: We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organizations.

Applications and interviews are managed by Constellation, our recruiting partner. Clicking "Apply here" will take you to their portal, and updates will come from a Constellation address. Constellation also runs the Berkeley workspace and provides program support for fellows working on AI safety and security; fellows on capabilities-focused projects are supported directly by Anthropic. All applicants currently use the same application portal but we are working to separate applications for safety/security and capabilities focused projects in future rounds.

Apply here

The below are Anthropic's policies for full time roles. These do NOT apply to the Fellows Program.

Apply using this link. We are accepting applications on a rolling basis for the next cohort of Anthropic Fellows, which is expected to start in late September. In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the September start date doesn't work for you.

This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting.

Anthropic Fellows Program overview

The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience.

Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers.

We run multiple cohorts of Fellows each year and review applications on a rolling basis. This application is for cohorts starting in July 2026 and beyond.

What to expect

• 4 months of full-time research 
• Direct mentorship from Anthropic researchers 
• Access to a shared workspace (in either Berkeley, California or London, UK)
• Connection to the broader AI safety and security research community
• Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country)
• Funding for compute (~$15k/month) and other research expenses

Interview process

The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion. 

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. 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.

Compensation

The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension).

Fellows workstreams

Due to the success of the Anthropic Fellows for AI Safety Research program, we are now expanding it across teams at Anthropic. We expect there to be significant overlap in the types of skills and responsibilities across the roles and will by default consider candidates for all the workstreams.

Some of the workstreams may include unique assessment steps; we therefore ask you for workstream preferences in the application. You can see an overview of the current workstreams below:

1. AI Safety Fellows
2. AI Security Fellows
3. ML Systems & Performance Fellows
4. Reinforcement Learning Fellows
5. Economics & Societal Impacts Fellows

This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting.

Across the workstreams, you may be a good fit if you:

• Are motivated by making sure AI is safe and beneficial for society as a whole
• Are excited to transition into empirical AI research and would be interested in a full-time role at Anthropic
• Have a strong technical background in computer science, mathematics, or physics
• Thrive in fast-paced, collaborative environments
• Can implement ideas quickly and communicate clearly

Strong candidates may also have:

• Strong background in a discipline relevant to a specific Fellows workstream (e.g. economics, social sciences, or cybersecurity)
• Experience in areas of research or engineering related to their workstream

Candidates must be:

• Fluent in Python programming
• Available to work full-time on the Fellows program

AI Security Fellows

Mentors, research areas, & past projects

Fellows will undergo a project selection & mentor matching process. Potential mentors include:

• Nicholas Carlini
• Keri Warr
• Evyatar Ben Asher
• Keane Lucas
• Newton Cheng

On our Alignment Science and Frontier Red Team blogs, you can read about some past Fellows projects, including:

• AI agents find $4.6M in blockchain smart contract exploits: Winnie Xiao and Cole Killian, mentored by Nicholas Carlini and Alwin Peng
• Strengthening Red Teams: A Modular Scaffold for Control Evaluations: Chloe Loughridge et al., mentored by Jon Kutasov and Joe Benton

Unique candidate criteria

You might be a particularly great fit for this workstream if you:

• Are motivated by reducing catastrophic risks from advanced AI systems
• Have contributed to open-source projects in LLM- or security-adjacent repositories
• Have demonstrated success in bringing clarity and ownership to ambiguous technical problems
• Have experience with pentesting, vulnerability research, or other offensive security work
• Have a demonstrated willingness to do the "dirty work" that produces high-quality outputs
• Have reported CVEs or been awarded bug bounties
• Have experience with empirical ML research projects
• Have experience with deep learning frameworks and experiment management

Logistics

Logistics Requirements: To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program.

Workspace Locations: We have designated shared workspaces in London and Berkeley where fellows will work from and mentors will visit. We are also open to remote fellows in the UK, US, or Canada. We will ask you about your availability to work from Berkeley or London (full- or part-time) during the program.

Visa Sponsorship: We are not currently able to sponsor visas for fellows. To participate in the Fellows program, you need to have or independently obtain full-time work authorization in the UK, the US, or Canada.

Program Duration: The program runs for 4 months, full-time. If you can't commit to the full duration, please still apply and note your constraints in the application. We review these requests on a case-by-case basis.

Please note: We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organizations.

Applications and interviews are managed by Constellation, our recruiting partner. Clicking "Apply here" will take you to their portal, and updates will come from a Constellation address. Constellation also runs the Berkeley workspace and provides program support for fellows working on AI safety and security; fellows on capabilities-focused projects are supported directly by Anthropic. All applicants currently use the same application portal but we are working to separate applications for safety/security and capabilities focused projects in future rounds.

Apply here

The below are Anthropic's policies for full time roles. These do NOT apply to the Fellows Program.

Apply using this link. We are accepting applications on a rolling basis for the next cohort of Anthropic Fellows, which is expected to start in late September. In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the September start date doesn't work for you.

This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting.

Anthropic Fellows Program overview

The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience.

Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers.

We run multiple cohorts of Fellows each year and review applications on a rolling basis. This application is for cohorts starting in July 2026 and beyond.

What to expect

• 4 months of full-time research 
• Direct mentorship from Anthropic researchers 
• Access to a shared workspace (in either Berkeley, California or London, UK)
• Connection to the broader AI safety and security research community
• Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country)
• Funding for compute (~$15k/month) and other research expenses

Interview process

The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion. 

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. 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.

Compensation

The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension).

Fellows workstreams

Due to the success of the Anthropic Fellows for AI Safety Research program, we are now expanding it across teams at Anthropic. We expect there to be significant overlap in the types of skills and responsibilities across the roles and will by default consider candidates for all the workstreams.

Some of the workstreams may include unique assessment steps; we therefore ask you for workstream preferences in the application. You can see an overview of the current workstreams below:

1. AI Safety Fellows
2. AI Security Fellows
3. ML Systems & Performance Fellows
4. Reinforcement Learning Fellows
5. Economics & Societal Impacts Fellows

This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting.

Across the workstreams, you may be a good fit if you:

• Are motivated by making sure AI is safe and beneficial for society as a whole
• Are excited to transition into empirical AI research and would be interested in a full-time role at Anthropic
• Have a strong technical background in computer science, mathematics, or physics
• Thrive in fast-paced, collaborative environments
• Can implement ideas quickly and communicate clearly

Strong candidates may also have:

• Strong background in a discipline relevant to a specific Fellows workstream (e.g. economics, social sciences, or cybersecurity)
• Experience in areas of research or engineering related to their workstream

Candidates must be:

• Fluent in Python programming
• Available to work full-time on the Fellows program

AI Safety Fellows

Mentors, research areas, & past projects

Fellows will undergo a project selection & mentor matching process. Potential mentors include:

• Sam Bowman
• Sara Price
• Alex Tamkin
• Nina Panickssery
• Trenton Bricken
• Logan Graham
• Jascha Sohl-Dickstein
• Joe Benton
• Collin Burns
• Fabien Roger
• Samuel Marks
• Kyle Fish
• Ethan Perez

Our mentors will lead projects in select AI safety research areas, such as:

• Scalable Oversight: Developing techniques to keep highly capable models helpful and honest, even as they surpass human-level intelligence in various domains.
• Adversarial Robustness and AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios.
• Model Organisms: Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise.
• Model Internals / Mechanistic Interpretability: Advancing our understanding of the internal workings of large language models to enable more targeted interventions and safety measures.
• AI Welfare: Improving our understanding of potential AI welfare and developing related evaluations and mitigations.

On our Alignment Science and Frontier Red Team blogs, you can read about past projects, including:

• Subliminal Learning: Language Models Transmit Behavioral Traits via Hidden Signals in Data: Alex Cloud and Minh Le, et al., mentors including Samuel Marks and Owain Evans
• Open-source circuits: Michael Hanna and Mateusz Piotrowski with mentorship from Emmanuel Ameisen and Jack Lindsey

For a full list of representative projects for each area, please see these blog posts: Introducing the Anthropic Fellows Program for AI Safety Research, Recommendations for Technical AI Safety Research Directions.

Unique candidate criteria

You might be a particularly great fit for this workstream if you:

• Are motivated by reducing catastrophic risks from advanced AI systems
• Have experience with empirical ML research projects
• Have experience working with large language models
• Have experience in one of the research areas mentioned above
• Have a track record of open-source contributions

Logistics

Logistics Requirements: To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program.

Workspace Locations: We have designated shared workspaces in London and Berkeley where fellows will work from and mentors will visit. We are also open to remote fellows in the UK, US, or Canada. We will ask you about your availability to work from Berkeley or London (full- or part-time) during the program.

Visa Sponsorship: We are not currently able to sponsor visas for fellows. To participate in the Fellows program, you need to have or independently obtain full-time work authorization in the UK, the US, or Canada.

Program Duration: The program runs for 4 months, full-time. If you can't commit to the full duration, please still apply and note your constraints in the application. We review these requests on a case-by-case basis.

Please note: We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organizations.

Applications and interviews are managed by Constellation, our recruiting partner. Clicking "Apply here" will take you to their portal, and updates will come from a Constellation address. Constellation also runs the Berkeley workspace and provides program support for fellows working on AI safety and security; fellows on capabilities-focused projects are supported directly by Anthropic. All applicants currently use the same application portal but we are working to separate applications for safety/security and capabilities focused projects in future rounds.

Apply here

The below are Anthropic's policies for full time roles. These do NOT apply to the Fellows Program.

Apply using this link. We are accepting applications on a rolling basis for the next cohort of Anthropic Fellows, which is expected to start in late September. In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the September start date doesn't work for you.

Anthropic Fellows Program overview

The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience.

Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers.

We run multiple cohorts of Fellows each year and review applications on a rolling basis. This application is for cohorts starting in July 2026 and beyond.

What to expect

• 4 months of full-time research 
• Direct mentorship from Anthropic researchers 
• Access to a shared workspace (in either Berkeley, California or London, UK)
• Connection to the broader AI safety and security research community
• Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country)
• Funding for compute (~$15k/month) and other research expenses

Interview process

The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion. 

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. 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.

Compensation

The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension).

Fellows workstreams

Due to the success of the Anthropic Fellows for AI Safety Research program, we are now expanding it across teams at Anthropic. We expect there to be significant overlap in the types of skills and responsibilities across the roles and will by default consider candidates for all the workstreams.

Some of the workstreams may include unique assessment steps; we therefore ask you for workstream preferences in the application. You can see an overview of the current workstreams below:

1. AI Safety Fellows
2. AI Security Fellows
3. ML Systems & Performance Fellows
4. Reinforcement Learning Fellows
5. Economics Fellows

Across the workstreams, you may be a good fit if you:

• Are motivated by making sure AI is safe and beneficial for society as a whole
• Are excited to transition into empirical AI research and would be interested in a full-time role at Anthropic
• Have a strong technical background in computer science, mathematics, or physics
• Thrive in fast-paced, collaborative environments
• Can implement ideas quickly and communicate clearly

Strong candidates may also have:

• Strong background in a discipline relevant to a specific Fellows workstream (e.g. economics, social sciences, or cybersecurity)
• Experience in areas of research or engineering related to their workstream

Candidates must be:

• Fluent in Python programming
• Available to work full-time on the Fellows program

AI Safety Fellows

Mentors, research areas, & past projects

Fellows will undergo a project selection & mentor matching process. Potential mentors include:

• Sam Bowman
• Sara Price
• Alex Tamkin
• Nina Panickssery
• Trenton Bricken
• Logan Graham
• Jascha Sohl-Dickstein
• Joe Benton
• Fabien Roger
• Samuel Marks
• Kyle Fish
• Ethan Perez

Note: You may research mentors' prior work, but all applications must go through the official form, not the mentors.

Our mentors will lead projects in select AI safety research areas, such as:

• Scalable Oversight: Developing techniques to keep highly capable models helpful and honest, even as they surpass human-level intelligence in various domains.
• Adversarial Robustness and AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios.
• Model Organisms: Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise.
• Model Internals / Mechanistic Interpretability: Advancing our understanding of the internal workings of large language models to enable more targeted interventions and safety measures.
• AI Welfare: Improving our understanding of potential AI welfare and developing related evaluations and mitigations.

On our Alignment Science and Frontier Red Team blogs, you can read about past projects, including:

• Subliminal Learning: Language Models Transmit Behavioral Traits via Hidden Signals in Data: Alex Cloud and Minh Le, et al., mentors including Samuel Marks and Owain Evans
• Open-source circuits: Michael Hanna and Mateusz Piotrowski with mentorship from Emmanuel Ameisen and Jack Lindsey

For a full list of representative projects for each area, please see these blog posts: Introducing the Anthropic Fellows Program for AI Safety Research, Recommendations for Technical AI Safety Research Directions.

Unique candidate criteria

You might be a particularly great fit for this workstream if you:

• Are motivated by reducing catastrophic risks from advanced AI systems
• Have experience with empirical ML research projects
• Have experience working with large language models
• Have experience in one of the research areas mentioned above
• Have a track record of open-source contributions

AI Security Fellows

Mentors, research areas, & past projects

Fellows will undergo a project selection & mentor matching process. Potential mentors include:

• Nicholas Carlini
• Keri Warr
• Evyatar Ben Asher
• Keane Lucas
• Newton Cheng

On our Alignment Science and Frontier Red Team blogs, you can read about some past Fellows projects, including:

• AI agents find $4.6M in blockchain smart contract exploits: Winnie Xiao and Cole Killian, mentored by Nicholas Carlini and Alwin Peng
• Strengthening Red Teams: A Modular Scaffold for Control Evaluations: Chloe Loughridge et al., mentored by Jon Kutasov and Joe Benton

Unique candidate criteria

You might be a particularly great fit for this workstream if you:

• Are motivated by reducing catastrophic risks from advanced AI systems
• Have contributed to open-source projects in LLM- or security-adjacent repositories
• Have demonstrated success in bringing clarity and ownership to ambiguous technical problems
• Have experience with pentesting, vulnerability research, or other offensive security work
• Have a demonstrated willingness to do the "dirty work" that produces high-quality outputs
• Have reported CVEs or been awarded bug bounties
• Have experience with empirical ML research projects
• Have experience with deep learning frameworks and experiment management

ML Systems & Performance Fellows

Mentors, research areas, & past projects

Fellows will undergo a project selection & mentor matching process. Potential mentors include:

• Alwin Peng
• Zygi Straznickas

For a past example of an engineering-heavy project, see:

• AI agents find $4.6M in blockchain smart contract exploits

Projects in this workstream may include:

• Building a CPU simulator for accelerator workloads
• Adding backends for different accelerators on an open source project
• Building on demand infrastructure for other infrastructure heavy fellows projects 
• Building complex synthetic data or environment pipelines

Unique candidate criteria

You might be a particularly great fit for this workstream if you:

• Have strong software engineering skills with experience building complex ML systems
• Can balance research exploration with engineering rigor and operational reliability
• Enjoy collaborating across research and engineering disciplines
• Are comfortable working with large-scale distributed systems and high-performance computing (e.g. in trading)
• Have experience with training, fine-tuning, or evaluating large language models
• Are adept at analyzing and debugging model training processes

Reinforcement Learning Fellows

Mentors, research areas, & past projects

Fellows will undergo a project selection & mentor matching process. Potential research areas and mentors include:

• Ruhua Jiang
• Kaidi Cao
• Sunny Duan
• David Brandfonbrener
• Colt Steele
• Dino Distefano
• Will Williams

Projects in this workstream may include:

• Building model-based tools to better understand AI training data and improve training data quality
• A research project to better understand generalization
• Creating RL environments to improve Claude models at capabilities that are within your domain of expertise
• Building RL environments for safety-related tasks
• Conducting research and implementing solutions in areas such as RL algorithms

Unique candidate criteria

You might be a particularly great fit for this workstream if you:

• Have strong software engineering skills with experience building complex ML systems
• Can balance research exploration with engineering rigor and operational reliability
• Enjoy collaborating across research and engineering disciplines
• Are comfortable working with large-scale distributed systems and high-performance computing
• Have experience with training, fine-tuning, or evaluating large language models
• Are adept at analyzing and debugging model training processes

The Anthropic Institute Fellows (Economics & Policy)

Mentors, research areas, & past projects

Fellows will undergo a project selection & mentor matching process. Potential research areas and mentors include:

• Economics
  • Maxim Massenkoff
  • Peter McCrory
• Policy, Security, and Society
  
  • Jack Clark
  • Marina Favaro
  • Jim Baker

Projects in this workstream may include:

• Designing and conducting empirical research on AI's economic effects, drawing on external data sources
• Developing new methodological approaches for studying AI's impact on labor markets, the future of work, and society
• Analysing the offense–defense balance for AI-enabled cyber and bio capabilities as models scale
• Measuring the extent to which model performance increases with custom harnesses?
• Identifying market driven mechanisms that could improve societal resilience to anticipated threats from AI systems?
• Identifying which metrics relating to AI R&D could service as early warning signals for recursive self-improvement

For past project examples, see:

• How AI Impacts Skill Formation: Judy Shen and Alex Tamkin
• Stress-Testing Model Specs Reveals Character Differences among Language Models: Jifan Zhang, Henry Sleight, Andi Peng, John Schulman, and Esin Durmus

Unique candidate criteria

You might be a particularly great fit for this workstream if you:

• Have an interest in economics or policy research; prior experience in this area is a plus but not required
• Are adaptable and collaborative, able to take direction and contribute to team priorities rather than needing to pursue a predetermined research agenda
• Are skilled at writing up and communicating your results, even when they're null or unexpected
• Are passionate about translating research insights into actionable recommendations for improving AI systems and informing policy

Logistics

Logistics Requirements: To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program.

Workspace Locations: We have designated shared workspaces in London and Berkeley where fellows will work from and mentors will visit. We are also open to remote fellows in the UK, US, or Canada. We will ask you about your availability to work from Berkeley or London (full- or part-time) during the program.

Visa Sponsorship: We are not currently able to sponsor visas for fellows. To participate in the Fellows program, you need to have or independently obtain full-time work authorization in the UK, the US, or Canada.

Program Duration: The program runs for 4 months, full-time. If you can't commit to the full duration, please still apply and note your constraints in the application. We review these requests on a case-by-case basis.

Please note: We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organizations.

Applications and interviews are managed by Constellation, our recruiting partner. Clicking "Apply here" will take you to their portal, and updates will come from a Constellation address. Constellation also runs the Berkeley workspace and provides program support for fellows working on AI safety and security; fellows on capabilities-focused projects are supported directly by Anthropic. All applicants currently use the same application portal but we are working to separate applications for safety/security and capabilities focused projects in future rounds.

Apply here

The below are Anthropic's policies for full time roles. These do NOT apply to the Fellows Program.

Responsibilities:

• Designing and implementing from scratch new information architecture strategies
• Performing finetuning and reinforcement learning to teach language models how to interact with new information architectures
• Building “hard” knowledge base eval sets to help identify failure modes of how language models work with external data
• Designing and evaluating advanced agentic search capabilities.

You may be a good fit if you:

• Are a very experienced Python programmer who can quickly produce reliable, high quality code that your teammates love using
• Have good machine learning research experience 
• Have experience developing software that utilizes Large Language Models such as Claude
• 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 partner with world-class ML researchers to develop new LLM capabilities
• Care about the societal impacts of your work
• Have clear written and verbal communication

Strong candidates will also have experience with:

• Collaborating with product teams to quickly prototype and deliver innovative solutions
• Building complex agentic systems that utilize LLMs
• Developing scalable distributed information retrieval systems, such as search engines, knowledge graphs, RAG, indexing, ranking, query understanding, and distributed data processing

About the role

Every time Anthropic releases a model, we publish a system card: a long-form technical document that describes the model's capabilities, safety properties, evaluation results, and the reasoning behind our deployment decisions. System cards are some of the most consequential and widely read documents we produce, and they are one way we hold ourselves publicly accountable for the safety claims we make.

We're hiring a Research Operations Specialist to help own system card production. You'll work embedded with research and safety teams through each launch, coordinating contributions from dozens of researchers, holding the schedule and the open-threads list, and making sure the document ships on time as a single, accurate, internally consistent whole. Along the way you'll do real editorial work: turning results and researcher notes into clear, honest prose and pushing back when an explanation doesn't hold together.

System cards sit within a wider family of external safety artifacts, including risk reports and Responsible Scaling Policy updates. Part of this role is keeping the system card consistent with those documents so that Anthropic's public safety story reads as one coherent account rather than several.

This role sits in Research Operations and works closely with Alignment, Safeguards, Frontier Red Team, and capabilities research. The core of the job is part project management, part translation: keeping a complex, many-author, hard-deadline document on track while making frontier safety research legible to researchers, policymakers, journalists, and the public — without sacrificing precision.

Key responsibilities:

• Drive system card production end to end — own the timeline, the contributor list, the open-threads tracker, and the definition of done for each launch
• Coordinate dozens of contributors across Alignment, Safeguards, Frontier Red Team, Interpretability, and capabilities; chase drafts, resolve differences of perspective, seek ground truth, and run final document beautification
• Edit, and sometimes write, content; work directly with researchers to turn their results, notes, and plots into clear, scientific, non-marketing prose and maintain Anthropic's voice across sections drafted by many different people
• Guard accuracy and consistency; catch terminology drift, claims that subtly contradict each other, and discrepancies between internal communications and system card drafts
• Keep the system card aligned with related artifacts; track what's being said in risk reports, RSP disclosures, and other safety documentation so the system card stays consistent with them, and flag conflicts early
• Improve the process between launches; build and maintain templates, style guidance, contributor guides, checklists, and reusable section scaffolds so each cycle starts from a stronger baseline
• Pick up other research-adjacent operations and writing, such as internal research summaries, release notes, and documentation that helps research leadership communicate clearly

Minimum qualifications:

• Strong project management and execution skills; able to track dozens of open threads to closure during compressed launch periods with many moving parts and many owners
• Demonstrated ability to coordinate and influence without direct authority, building trust while chasing drafts and giving constructive editorial feedback
• Excellent technical writing skills; able to take dense, jargon-heavy source material and produce prose that is precise, honest, and readable by a smart non-specialist
• Comfort working closely with researchers; able to read an evaluation results table, ask the right clarifying questions, and push back when an explanation doesn't hold together
• Working knowledge of large language models at a conceptual level, including fluency with vocabulary such as pretraining, RLHF, context windows, evals, and red-teaming
• Data communication literacy; able to identify how a chart or table could be made clearer and more accurate
• High integrity and a genuine sense of accountability around producing documents that hold Anthropic publicly responsible for its safety claims

Preferred qualifications:

• Familiarity with AI safety, AI policy, alignment research, evaluation methodology, or the RSP landscape beyond baseline LLM knowledge
• Background in science communication, research publishing, or technical journalism
• A track record of shipping long-form technical documents: research reports, whitepapers, technical standards, regulatory filings, or science journalism
• Experience with safety, risk, or compliance documentation such as regulatory submissions, safety cases, security disclosures, or clinical/scientific reporting
• An eye for visual communication and experience shipping polished, on-brand documents
• Light scripting or tooling ability (enough to automate a formatting check or wrangle a spreadsheet)

About the UX research team

UX research at Anthropic is a small team with outsized leverage. We work across products used by millions of people—and on interactions that don't have established conventions yet.

We inform critical decisions through rigorous research, with stakeholders who eagerly incorporate findings into their work. Research has a seat at the table for product strategy, and we partner closely with design, product, and engineering. We combine qualitative and quantitative methods to understand user needs in a space that's evolving faster than anyone can track.

We move fast, favor impact over polish, and increasingly build our own tools—often with AI doing the heavy lifting—to do research at the speed this environment demands.

About this role

This is a senior individual-contributor role. You'll own research for a complex, fast-moving product area where the surface is expanding quickly and the most important user questions haven't been articulated yet, let alone answered.

You won't work from a fixed research roadmap. You'll prioritize constantly—making clear, well-informed bets about what to learn next, executing on them fast, and pivoting the moment the picture changes. Our product teams are deeply technical and move on instinct; your job is to make that instinct better-calibrated without slowing it down.

Roles here are fluid. On any given week you might be the researcher, the analyst, the one framing the next product bet, or the one building a prototype because that's the fastest way to find out.

Where this role lands depends on team needs and your strengths—we'll figure that out together.

Responsibilities

• Set the research agenda for a product area where the strategic questions are still fuzzy. Define what we need to learn, in what order, and why—then go learn it. Don't wait to be asked
• Design and run mixed-methods research at whatever fidelity the moment calls for. Some of it will be careful, foundational work the team references for a year. Some of it will be a finding you ship the same day the question came up
• Keep product teams close to users in a rigorous way—building the channels, cadence, and evidence base that make user reality hard to ignore
• Get hands-on with product data. Pull your own samples, build your own dashboards, instrument what's missing
• Prototype when prototyping is the fastest path to an answer—a research tool, a survey pipeline, a scrappy version of a feature to put in front of users
• Deeply leverage AI in how you work—using Claude to make yourself dramatically more efficient at analysis, synthesis, tooling, and everything in between
• Use what you study. Dogfood our products hard enough to develop your own informed opinions, and bring that texture into your research
• Anticipate where the product is heading before anyone asks. Show up with the user understanding the team is about to need
• Turn what you learn into recommendations confident enough to redirect a roadmap—including recommending we kill something that isn't working
• Build durable understanding, not just findings. The goal is that PMs, designers, and engineers internalize the user mental model well enough to make good calls when you're not in the room
• Develop new research methods when the existing playbook doesn't fit—particularly methods that use AI to do things that weren't possible before

Qualifications

• Industry UX research experience, including ownership of research strategy for a product or product area
• Track record of research that shifted product direction at the strategy level, not just the feature level
• Deep mixed-methods expertise—qualitative and quantitative
• Enough data fluency to use Claude to work directly with our data warehouse—pulling your own samples, writing your own queries, running your own analyses
• Demonstrated technical range: you've built research tooling, prototyped, scripted analyses, or otherwise shown you can keep up with very technical teams without translation overhead
• Advanced, hands-on use of AI in your own research workflow—you're already taking full advantage of its capabilities to enhance how you work
• Experience embedding with engineering-led product teams that ship fast, and earning influence in that environment
• Excellent storytelling, calibrated to audience. You can discuss a finding with an exec as effectively as with an engineer

About the role

As Anthropic's Lead for Data Center Security Operations in North America, you will own the physical security program across our NA data center footprint — spanning owned sites and colocation partners. You will partner closely with data center build and operations teams from the earliest design conversations through commissioning and into steady-state operations, shaping the security posture that protects some of the most consequential AI compute in the industry.

This role is hands-on and strategic at the same time. You'll be on-site when it matters, author the policies and standards that govern the region, run the vendor and guard-force relationships that keep our sites secure day-to-day, and lead incident response when something happens. You'll also be one of the primary regional voices shaping how security integrates with infrastructure, compute, real estate, and legal partners as Anthropic scales.

You will join a growing Data Center Security Engineering function that is still in build mode. The work is ambiguous, fast-moving, and changes as strategy changes. We need someone who can set direction without waiting for mature playbooks, and who treats security as an enabler of business outcomes.

Responsibilities

You will own a region of North America data center security operations program across owned and colocation sites. 

• You'll partner with data center build and engineering teams on new-site design and activation, ensuring security scope is defined, delivered, and turned over to operations cleanly. 
• You'll lead the regional vendor portfolio such as integrators, guard-force providers, and general contractors with meaningful budget and SLA ownership. 
• You'll author and maintain the policies, standards, and SOPs that govern physical security in the region, keeping them aligned with company-wide frameworks. 
• You'll lead physical security incident response and investigations, and you'll represent the region in cross-functional forums that shape infrastructure, compute, and real estate decisions. 

You may be a good fit if you

• Have extensive experience operating physical security at hyperscale or at a major colocation operator across multiple sites, with direct ownership of the operating model, vendors, and on-call.
• Have personally led the security scope on new-build data center projects from design through construction, commissioning, and turnover to operations.
• Have worked across both owned data centers and colocation space, and understand how the operator/tenant dynamic changes your controls, vendors, and incident response.
• Can author physical security policies, standards, and SOPs that get adopted and followed.  
• Drive security outcomes through cross-functional partners (infrastructure, construction, real estate, compliance, legal) by shaping decisions, not by blocking them.
• Manage a real vendor portfolio, integrators, guard force, general contractors with SLAs, budget, and performance accountability.
• Adapt well when design and strategy shift mid-stream and can re-scope a program without losing momentum.
• Calibrate security to business reality can explain when you chose not to apply a control and why.

Strong candidates may have

• CPP (Certified Protection Professional) or PSP (Physical Security Professional) certification.
• Experience standing up a data center security function from 0→1 (not just running an established one).
• Background in a regulated environment, critical infrastructure, financial services, federal/defense, or similar.
• Direct experience leading an external audit or customer security review of data center physical controls.

Strong candidates need not have

• A specific university, credential, or prior employer. We care about what you've built and operated, not where.
• Prior people-management experience, this role is an IC lead today. If you've led matrixed or virtual teams, that's enough.
• Experience in AI or machine learning infrastructure specifically we'll teach you how our workloads shape the security posture.

Deadline to apply: None. Applications will be received on a rolling basis.

About the role

We are hiring a Strategic Sourcing Lead to drive development and execution of procurement strategies for the network infrastructure that powers Anthropic's data centers. In this role, you will own end-to-end sourcing for the full network stack — switching and routing platforms, optics and transceivers, structured cabling and fiber, and long-haul connectivity (dark fiber, IP transit, DCI). You will partner closely with network engineering, capacity planning, and third-party vendors to ensure hardware and bandwidth availability, establish strategic vendor relationships, and negotiate commercial agreements. As the sourcing lead for Anthropic's network footprint, you will play a critical role in helping us achieve our ambitious scaling goals.

Responsibilities:

• Drive commercial negotiations and Master Service Agreements with network OEMs (switching/routing platforms, optical equipment, network appliances) and connectivity providers (carriers, dark fiber operators, IP transit and peering partners).

• Audit network OEM and carrier procurement schedules, ensure optimal allocation, and drive cost efficiency of supply in constrained markets (especially high-demand items like 400G/800G optics and high-radix switches).

• Implement frameworks to ensure third-party data center and network partners adhere to commercial terms and technical specifications.

• Develop a global inventory strategy for network gear and optics — including warehousing, third-party logistics, buffer stock, and regional distribution — to accelerate time-to-deployment and improve availability.

• Proactively monitor global network supply chain volatility (silicon shortages, optics lead times, fiber availability) and execute contingency plans to avoid critical project delays.

• Translate network architecture roadmaps into equipment and connectivity forecasts and procurement pipelines.

• Partner with Finance to optimize network inventory strategy and capex planning.

• Establish efficient return and replacement (RMA) workflows with network vendors to restore failed equipment quickly.

• Negotiate warranty and SLA terms and track vendor performance on RMA execution and circuit delivery.

You may be a good fit if you:

• Have 7+ years of experience in supply chain management, sourcing, and procurement.

• Have a track record of developing processes for forecasting, planning, and managing network material and connectivity for data center build-out and/or operations.

• Are familiar with data center networking hardware and connectivity (e.g., switches, routers, optics/transceivers, structured cabling, dark fiber, transit, peering).

• Possess a bachelor's degree in a relevant domain or equivalent practical experience.

It's a bonus if you have:

• 10+ years of experience in supply chain management, sourcing, and procurement.

• 5+ years of experience sourcing data center network infrastructure.

• Experience working with network OEMs, integrators, optics suppliers, and carriers.

• Experience working on large-scale network build-out programs (greenfield data center networks, DCI expansion, etc.).

• Leadership and influencing skills.

About the Role

We are looking for biological scientists to help build safety and oversight mechanisms for our AI systems. As a Safeguards Biological Safety Research Scientist, you will apply your technical skills to design and develop our safety systems which detect harmful behaviors and to prevent misuse by sophisticated threat actors. You will be at the forefront of defining what responsible AI safety looks like in the biological domain, working across research, policy, and engineering to translate complex biosecurity concepts into concrete technical safeguards. This is a unique opportunity to shape how frontier AI models handle dual-use biological knowledge—balancing the tremendous potential of AI to accelerate legitimate life sciences research while preventing misuse by sophisticated threat actors.

In this role, you will:

• Design and execute capability evaluations ("evals") to assess the capabilities of new models
• Collaborate closely with internal and external threat modeling experts to develop training data for our safety systems, and with ML engineers to train these safety systems, optimizing for both robustness against adversarial attacks and low false-positive rates for legitimate researchers
• Analyze safety system performance in traffic, identifying gaps and proposing improvements
• Develop rigorous stress-testing of our safeguards against evolving threats and product surfaces
• Partner with Research, Product, and Policy teams to ensure biological safety is embedded throughout the model development lifecycle
• Contribute to external communications, including model cards, blog posts, and policy documents related to biological safety
• Monitor emerging technologies for their potential to contribute to new risks and new mitigation strategies, and strategically address these

You may be a good fit if you have

• A PhD in molecular biology, virology, microbiology, biochemistry, systems or computational biology, or a related life sciences field, OR equivalent professional experience 
• Extensive experience in scientific computing and data analysis, with proficiency in programming (Python preferred)
• Deep expertise in modern biology, including both "reading" (e.g. high-throughput measurement, functional assays) and "writing" (gene synthesis, genome editing, strain construction, protein engineering) techniques in biology
• Familiarity with dual-use research concerns, select agent regulations, and biosecurity frameworks (e.g., Biological Weapons Convention, Australia Group guidelines)
• Strong analytical and writing skills, with the ability to navigate ambiguity and explain complex technical concepts to non-technical stakeholders
• Have a passion for learning new skills and an ability to rapidly adapt to changing techniques and technologies
• Comfort working in a fast-paced environment where priorities may shift as AI capabilities evolve

Preferred Qualifications

• Background in AI/ML systems, particularly experience with large language models
• Experience in developing ML for biological systems
• Extensive experience in complex projects with multiple stakeholders

About the role

As a Senior Data Center Capacity Delivery Manager at Anthropic, you'll embed with project teams responsible for delivery of leased and partnered data center capacity. Your primary role will be to lead these partners to deliver on the fastest possible schedule while maintaining a safe construction site and protecting the finished quality of the data center.

Additionally, you'll validate deal readiness, coordinate complex stakeholder relationships, maintain regular reporting and status tracking, and ensure seamless transitions from project inception through operational readiness. 

This role offers a unique opportunity to shape how Anthropic secures and activates the compute infrastructure needed to train and deploy frontier AI systems, working at the intersection of real estate, construction, and cutting-edge AI infrastructure.

Responsibilities

• Lead. This is a role where leadership trumps management and process. You will be at one or more project sites 60% of the time or more and expected to shape the culture, approach, and aggressiveness that define those extended site teams. The goal is to impact outcomes in a favorable manner.
• You are expected to be a force multiplier that develops and enhances the skillset that development partners, general contractors, and key trades bring to the project(s) you are overseeing. That means being a subject matter expert in the various cross functional elements of data center delivery and increasing the team's performance with that knowledge and commitment to alignment.
• Confirm deal readiness and serve as the gatekeeper to validate transaction viability from Letter of Intent (LOI) through lease execution, ensuring all predevelopment, planning, technical and business requirements are met before commitment
• Partner with landlords and developers post-deal to serve as Anthropic's primary point of contact, coordinating across internal stakeholders, tracking construction progress, and facilitating critical information exchange between development partners and Anthropic stakeholders
• Represent Anthropic in key technical and operational decisions required by partners during the development process, ensuring our infrastructure requirements are met while maintaining strong partnerships
• Drive seamless handoffs to operational state with heavy focus on engagement across networking and deployment teams, enabling rapid workload turn-ups and minimizing time-to-production
• Prepare and present regular executive reporting on progress versus plan for facility development, supporting forward capacity planning and strategic decision-making
• Identify and mitigate risks throughout the delivery lifecycle, proactively addressing blockers that could impact timeline, cost, or technical requirements
• Develop and refine standardized processes and playbooks for facility delivery, driving continuous improvement as Anthropic scales its infrastructure footprint

You may be a good fit if you

• Have 10+ years of experience in the highest level of site leadership managing data center delivery, construction projects, or infrastructure deployment at scale.  You won’t have a big direct team to delegate too but will instead be able to treat the entire cross functional organizations at a jobsite as your team.
• Have a strong understanding of the end to end (dirt to delivery) data center development process to include entitlements and permitting, planning and supply chain, execution, commissioning, and handover. You are not an administrator but an active player in the arena comfortable making decisions and guiding delivery execution without the need to consult across multiple external parties.
• You should understand data center design and construction as a simple and repeatable process that allows you to build and optimize delivery without a playbook and with minimal processes and tools handed to you.  If you can think about building a data center the way kids might build a tree fort or construct a lego set, we want to talk.

In this role you will often be on an island and responsible for your own destiny. You will have free reign to develop your own approaches with the mission guidance being your only bounds. No one will be there to empower your efforts; you will create your own influence by building relationships at the site and diving in at all phases to deliver success.

You must thrive operating with ambiguity and have a willingness to own project outcomes, knowing that the buck stops with you.

In this role, it is imperative that you are as comfortable in boots on a job site working to solve productivity issues with a group of blue collar trades as you are working across executives at development and contractor partners to optimize contract and commercial structures that incentivize delivery speed.

It's a bonus if you

• Understand AI/ML infrastructure requirements, including high-density power and advanced cooling systems
• Have had leadership positions (General Superintendent, Project Manager) within a GC or EPC on hyperscale data center projects or in self performance of hyperscale data center development projects.
• Prioritize extreme ownership and have the ability to create winning cultures across diverse job sites.
• Are deeply familiar with lease negotiations, construction contracts, or real estate development processes and have strategies to move those arrangements from traditionally transaction and risk managed arrangements to collaborative efforts that align incentives around accelerated delivery of facilities

About the role

As a Cluster Deployment Engineer, you will own how large-scale AI compute clusters physically come together inside our datacenter fleet. You will set the deployment-engineering strategy for cluster build-out — how racks are organized into pods, halls, and sites; how compute, network, power, and cooling systems interface at the rack boundary; and how deployment scope flows cleanly from hardware specification to facility delivery to a running cluster. This role is focused on deployment engineering, not on datacenter network or systems design — your scope is making sure clusters land cleanly and predictably, not designing the fabrics or facilities themselves.

This is a senior individual-contributor role with broad technical influence. You will work across hardware, networking, facilities, supply chain, and construction to ensure that every generation of accelerator we deploy lands in a datacenter that is ready for it — on schedule, at full density, and with every piece of required infrastructure accounted for. You will be the person who sees around corners: anticipating how next-generation rack designs will stress our facilities, where our deployment model will break at scale, and what needs to change now so that the next cluster turn-up is faster and more predictable than the last.

You will operate at the intersection of engineering strategy and execution discipline, partnering with internal research and systems teams, external developers, engineering firms, and OEM partners to deliver cluster capacity at the speed the frontier demands.

Responsibilities 

• Own cluster-level deployment strategy — define how AI compute clusters are organized across the floor, how racks interconnect, and how cluster topology requirements translate into facility and deployment scope across a portfolio of sites.

• Set rack interface standards spanning power, network, mechanical, thermal, and spatial domains, and ensure that every deployment includes the complete set of infrastructure required to bring a cluster online.

• Drive multi-threaded cluster bring-up programs across hardware, networking, power, and cooling — owning plans, dependencies, and critical paths from hardware specification through energization and turn-up.

• Partner with internal engineering teams — research, systems, networking, and hardware — to translate cluster requirements into deployable facility scope, and to derisk onboarding of new hardware platforms well ahead of delivery.

• Lead external partner execution with developers, engineering firms, OEMs, and construction teams, driving technical reviews, deviation management, and handoffs that keep deployments on schedule and within specification.

• Improve cluster turn-up reliability and repeatability — identify systemic gaps in deployment scope, tooling, and partner interfaces, and drive durable fixes that reduce time-to-serve for new capacity.

• Define and track deployment KPIs — cluster readiness, schedule adherence, scope completeness, time-to-first-packet — and use historical trends to forecast risk and inform capacity planning.

• Coordinate cross-functional readiness across supply chain, security, operations, and construction to ship production-ready compute capacity.

• Provide crisp executive visibility on deployment progress, tradeoffs, and risks across a portfolio of concurrent cluster programs.

• Design cluster interfaces for durability — define rack and cluster-level interfaces that remain robust across hardware generations, so that facility scope and deployment models do not need to be reinvented every time the underlying hardware changes.

• Build cluster layout and BOM tooling — create and maintain the tools, templates, and data models that turn cluster topology and rack specifications into accurate floor layouts, deployment sequences, and complete bills of materials, replacing one-off spreadsheets with repeatable, auditable workflows.

   

You may be a good fit if you

• Have 10+ years of experience in hyperscale datacenter environments, with senior-level responsibility for cluster deployment, large-scale IT integration, or equivalent infrastructure programs.

• Have delivered AI, HPC, or high-density compute clusters at scale and developed a strong intuition for the constraints that govern cluster deployment — interconnect reach, adjacency, power density, and thermal limits.

• Can operate fluently across the boundary between IT hardware and facility infrastructure, and have set interface standards that held up across multiple hardware generations and sites.

• Have led cross-functional programs with both internal engineering teams and external developers, engineering firms, and OEM partners, and are effective at driving alignment across organizational levels.

• Combine strong systems thinking with execution discipline — comfortable zooming from cluster topology and portfolio strategy down to the specific interface detail that will otherwise become a field issue.

• Communicate clearly with technical and executive audiences, and can distill complex, multi-disciplinary programs into decisions and tradeoffs leadership can act on.

• Thrive in ambiguous, fast-moving environments where the hardware, the scale, and the requirements are all changing simultaneously.

• Hold a Bachelor's degree in Electrical Engineering, Mechanical Engineering, Computer Engineering, or equivalent practical experience.

   

Strong candidates may also have

• Have direct experience deploying leading-edge AI accelerator clusters at hyperscale.

• Have shaped reference designs, deployment standards, or cluster-level playbooks that were adopted across a fleet.

• Have experience working across multiple geographies and understand how regional codes, climate, utility constraints, and supply chains shape cluster-level decisions.

• Have partnered closely with hardware and system providers on long-term platform onboarding and bring-up.

• Have experience building the program mechanisms — roadmaps, milestones, risk registers, runbooks — that make delivery predictable at massive scale.

About the role

As a Transaction Manager at Anthropic, you'll drive the commercial sourcing and transaction execution process for our data center capacity deals. You'll lead RFP processes, negotiate term sheets, and serve as the central leader ensuring seamless stakeholder alignment from initial sourcing through lease execution. This role is critical to securing the infrastructure that powers Anthropic's frontier AI systems, requiring you to bridge commercial negotiations with complex internal coordination across legal, finance, engineering, and network teams.

Responsibilities

• Help identify data center capacity opportunities and options through management of network relationships across data center developer, broker, and power contacts.

• Lead the RFP and commercial sourcing process for specific data center deals, managing developer outreach, proposal evaluation, and competitive selection processes

• Negotiate term sheets and manage the LOI process, structuring commercial terms that meet Anthropic's technical and business requirements while maintaining strong developer partnerships

• Create the bridge from LOI to executed transaction, ensuring all commercial, technical, and legal requirements are satisfied for deal closure

• Serve as project manager for cross-functional stakeholder engagement, coordinating due diligence teams, internal and external legal counsel, network organization, platform engineers, and finance organization to ensure alignment prior to lease execution

• Act as the single point of contact (SPOC) for auxiliary organizations including networks, deployments, and government relations, providing regular updates on transaction progress and leasing process status

• Develop and maintain transaction timelines, tracking critical path items and proactively identifying risks that could impact deal closure

• Document and refine transaction processes and playbooks to enable scalable deal execution as Anthropic expands its infrastructure footprint

• Ensure all stakeholder requirements are captured and addressed in commercial agreements, translating technical and operational needs into contractual terms

You may be a good fit if you

• Have 10+ years of experience in transaction management, commercial real estate, data center leasing, or infrastructure procurement

• Possess a proven track record of managing complex, multi-stakeholder transactions from sourcing through execution

• Have strong negotiation skills with experience structuring term sheets, LOIs, and commercial agreements

• Excel at project management and can coordinate across legal, technical, finance, and operational teams simultaneously

• Have experience with RFP processes and competitive sourcing for large-scale infrastructure or real estate transactions

• Demonstrate exceptional communication skills, able to serve as an effective liaison between internal stakeholders and external partners

• Are highly organized with strong attention to detail while maintaining focus on strategic deal objectives

• Can operate effectively in fast-paced, ambiguous environments where processes are being built alongside execution

• Have a collaborative mindset and can build trust with diverse stakeholder groups across the organization

It's a bonus if you

• Have experience with data center or hyperscale infrastructure transactions specifically

• Understand technical requirements for AI/ML workloads including power density, cooling, and network connectivity

• Have worked with legal teams on complex lease negotiations or infrastructure agreements

• Possess familiarity with data center developer ecosystems and market dynamics

• Have experience in high-growth technology companies managing infrastructure expansion

• Understand utility coordination, power procurement, or energy considerations in data center transactions

• Have a background in corporate development, strategic partnerships, or infrastructure investment

About the role 

As a Recruiting Coordinator at Anthropic, you'll be the engine that helps our recruiting efforts go, helping to schedule onsite interviews and moving candidates through the pipeline. As the first point of contact for many candidates, you'll help ensure new potential recruits have a positive experience with us. You'll play a key role in helping Anthropic assemble a talented staff to help us build reliable, interpretable and steerable AI systems. In collaboration with our recruiting team, you'll continuously improve our recruitment processes and candidate experience.

Responsibilities:

• In partnership with our recruiters, regularly schedule a high volume of candidate interviews, debriefs, and reference checks. Navigate complex scheduling scenarios to coordinate availability across multiple stakeholders

• Act as the primary point of contact for candidates, communicating externally with a warm and informative tone to provide a high-touch candidate experience. Ensure candidates feel supported and informed throughout their journey

• Support and suggest improvements to our recruitment processes in collaboration with other team members in often ambiguous situations. Identify opportunities to enhance efficiency and candidate satisfaction

• Drive the creation and implementation of new candidate experience programs and recruitment initiatives that enhance Anthropic's talent acquisition efforts and support the company's scaling hiring needs.

You may be a good fit if you have:

• 2+ years of experience in a high volume scheduling role, preferably in a recruiting or talent acquisition environment

• A passion for creating an exceptional candidate and hiring manager experience

• Excellent communication skills, especially a knack for writing friendly, informative emails that build rapport and convey information clearly

• The ability to excel in a fast-paced environment, where you are frequently responding to questions, requests, or other new action items

• A love of feedback and comfort both requesting and providing feedback to your colleagues

• Proactive problem-solving skills in ambiguous situations with the ability to quickly generate multiple potential solutions to challenging problems

• Experience acting as a strategic partner to Recruiters, helping them see around corners and suggesting improvements to their processes

• An interest in Anthropic's mission and our deep commitment to AI safety in research and product development

Work Details & Compensation:

• Base rate: $70 USD/hour

• Location: Fully remote position [please disregard the note below in regards to 25% in office]

• Duration: 6-month contract with potential for extension, no full-time conversions

• Employment through talent partner with dedicated benefits package

About the design team

Design at Anthropic sits at the intersection of craft, research, and product intuition. We're a small team working on products that millions of people use daily—and on interactions that don't have established conventions yet.

Our work shapes how people experience AI: whether Claude feels like a tool or a collaborator, whether it earns trust or erodes it. We partner closely with engineers and researchers, often designing around capabilities that are emerging in real-time. That means staying close to the models, prototyping rapidly, and being comfortable with ambiguity.

We care deeply about craft—the details that make something feel polished and trustworthy—but we ship fast and learn in the open. We'd rather get something in front of users and iterate than wait for perfection.

Read more here for the type of features we build. 

Responsibilities:

• Contribute to the strategic direction of our tools, rooted in deep user empathy
• Define feature areas with exceptional attention to detail and polish, identifying opportunities to improve quality and consistency of broader flows
• Craft beautiful, polished, and delightful user interfaces that build trust and showcase the power of our AI technology
• Collaborate with product managers, engineers, AI researchers and other stakeholders to define product vision, strategy and roadmaps
• Rapidly prototype ideas using code and other methods to communicate concepts and build excitement
• Find creative ways to ship high-quality work in a fast-paced, often ambiguous, resource-constrained startup environment

Specific projects & responsibilities depend on the team staffing, which we’ll talk about once we’ve seen some more of your work and understood your strengths & interests. A few examples across teams:

• Claude Cowork: Pioneer new ways for Claude to be a true partner in people’s day to day lives that can access your tools, ask for feedback, help you prep for your day, and more; Build expertise in industries like education, financial services, and healthcare to design intuitive experiences that help people leverage AI at work in transformative ways.
• Claude Code: Evolve our industry-leading coding tool, across terminal and Desktop, to deepen the breadth and depth of agentic coding.
• Growth: Design intuitive onboarding flows that help new users get started quickly, understand Claude's capabilities, and achieve their goals in the first session; Uncover barriers that prevent users from getting the most out of Claude and create experiences that empower them to make it a trusted part of their routine.
• Developer Platform: Support frontier capabilities and API features via tooling, workflows, and documentation; Define the future suite of utilities for developers to confidently build, monitor and control agentic systems.
• Consumer: Evolve the Claude mobile app, with a focus on being genuinely helpful for people’s everyday lives: learning, creative projects, personal planning and problem-solving — with an emphasis on quality & safety. 

What we’re looking for:

• You ship fast and stay in motion. You'd rather get something in front of users this week than perfect it for a month. You prototype in code, stay scrappy when speed matters, and know when to polish versus when to learn.
• You're rethinking the basics. Many UI primitives were designed for a different era. You're excited to question fundamental assumptions and invent patterns that feel native to AI.
• You're AI-native in how you work. You're already using Claude Code or similar tools to extend what you can build. You see AI as a creative partner in your own practice.
• You stay close to the models. You pay attention to where capabilities are heading, not just what Claude can do today. You design for the product we're becoming.
• You elevate craft while moving fast. You care about the details—the pixels, the copy, the edge cases—and find ways to maintain that care while shipping quickly.

You may be a good fit if you have:

• Experience designing complex workflows, enterprise/B2B SaaS, developer tools, or API products 
• Strong portfolio showcasing user-centric design thinking, polished UI craftsmanship, and innovative interaction paradigms
• Proven track record of executing end-to-end on large and complex products or a series of products in ambiguous environments
• Excellent collaboration and communication skills to work effectively with cross-functional teams and influence without authority
• Passion for crafting scaled, highly impactful, safe and beneficial artificial intelligence technologies to enable new possibilities
• Experience with prototyping, especially using front-end code (e.g. HTML/CSS/JS) preferred

About the role

Anthropic is rapidly scaling our compute infrastructure across a portfolio of datacenter builds with multiple developer, neocloud, and cloud partnerships. We're looking for a DC Portfolio Planning & Execution Lead to drive the planning and framework that ensures every site moves smoothly from the front-end phases through design, construction, equipment delivery, commissioning, and operational readiness.

This role owns the portfolio-level operating system: translating capacity supply pipeline into integrated project plans that span every phase of delivery, building the tooling and automation that runs it at scale, and maintaining Anthropic's datacenter capacity catalog — a lifecycle view of our fleet that supports both execution orchestration and steady-state capacity planning. You will build this function from the ground up.

Responsibilities

Portfolio schedule & catalog

• Manage the integrated master plan for each site across the portfolio — stitching power ramp, design, construction, sourcing, deployment, and operations readiness into a single coordinated schedule with clear milestones and dependencies

• Develop and maintain Anthropic's datacenter catalog for deployed and in-progress capacity. Manage the portfolio-level view of physical infrastructure & cluster interfaces across all sites and partners to enable planning decisions such as equipment fungibility, accelerator platforms, tech insertion, or workload allocation

Stage gates & execution tracking

• Define and run the stage gates and decision locks for cluster delivery — from lease execution to design lock through procurement, construction, equipment installation, commissioning, and handover

• Drive gate reviews, manage exceptions, and track the downstream impact of deviations across the portfolio

• Manage portfolio reviews and risk tracking for DC Infra leadership and Compute Supply

Tooling & process

• Develop tooling and automation to enable cross-functional planning flow-down from datacenter capacity availability dates

• Partner with Design, Supply Chain, Construction, and DC Ops program leads to drive cross-pillar process improvements as portfolio scales

You may be a good fit if you

• Are familiar with the full datacenter buildout lifecycle: pipeline → design → sourcing → construction → Cx → deployment

• Have run integrated portfolio or master-schedule planning across a fleet of capital projects (datacenter, energy, fab, or similar) where multiple functional orgs each own a phase

• Have built a stage-gate or decision-lock system from scratch and gotten functional leads to adopt it

• Have re-architected a deployment or delivery process at scale and can point to the cycle-time or throughput result

• Build the tooling yourself using AI-assisted development — stand up planning dashboards, schedule automation, and data pipelines from Smartsheet/P6/partner systems

• Proactively surface schedule risk across functions — comfortable flagging a problem in someone else's domain before it becomes a slip

• Track record of driving outcomes through influence with cross-functional partners

Strong candidates may also have

• Experience building a portfolio planning and execution function from scratch at a hyperscaler or large industrial owner

• Exposure to capacity planning or S&OP processes that connect demand forecast to physical build

• Experience product-managing internal planning, workflow, or scheduling systems

About the Role

As a Safeguards Policy Analyst focused on Fraud & Scams, you will be responsible for designing, building, and executing enforcement workflows that detect and mitigate fraud and scam-related harms on Anthropic's products. You will serve as the subject matter expert on fraud typologies, scam ecosystems, and the threat actors who perpetrate them — translating that expertise into durable and scalable policies. 

This role sits within the Integrity & Authenticity (I&A) team, You will function both as a policy owner, and work closely with threat investigative and enforcement teams.  You will also develop the guidelines that power classifiers, and will be our point of content  cross-functional workstreams. No two days will look the same.

Important context: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a financial, psychological, or otherwise disturbing nature, including detailed fraud schemes and scam content.

Responsibilities: 

Policy Design & Ownership

• Draft, maintain, and iterate on Fraud & Scams policies governing Anthropic's products and APIs, with clarity for both model enforcement and human reviewers
• Conduct regular structured policy reviews to identify gaps, ambiguities, and coverage failures, and lead the process to close them
• Develop detailed threat models for fraud and scam vectors — including social engineering, financial fraud, impersonation scams, phishing, and AI-enabled fraud — and translate these into enforceable policy language
• Stay current on the fraud and scam landscape, including emerging typologies, regulatory shifts, and threat actor tactics, techniques, and procedures (TTPs)

Enforcement Strategy & Operations

• Design and architect automated enforcement systems and human review workflows that scale effectively while maintaining high precision and recall
• Review flagged content to drive enforcement decisions and surface policy improvements grounded in real-world cases
• Define and manage precision/recall tradeoffs in enforcement, working with data science teams to continuously tune classifiers and detection signals
• Build and maintain an effective feedback loop between threat intelligence, policy, and enforcement operations to ensure timely response to novel and evolving fraud threats

Technical & Cross-functional Collaboration

• Serve as the primary policy point of contact for ML and Engineering teams developing fraud detection classifiers, working to translate policy intent into technical artifacts and training signals
• Partner with Product, Engineering, and Data Science teams to optimize detection models, automated enforcement pipelines, and tooling for fraud-specific policy violations
• Collaborate with external researchers, law enforcement liaisons, and fraud SMEs to gather feedback on policy effectiveness and emerging risk areas

Stakeholder Alignment & Education

• Educate and align internal stakeholders — including Legal, Public Policy, and Go-to-Market teams — around Anthropic's fraud and scams policies and enforcement approach
• Serve as an internal resource on fraud risk, briefing leadership and cross-functional partners as threats evolve
• Contribute to Anthropic's external communications and policy documentation related to fraud and platform integrity where relevant

You may be a good fit if you have experience:

• Working as a Trust & Safety professional with a focused background in fraud, scams, or financial crime — particularly in a tech platform or AI context
• Writing, iterating on, and managing operational policies for fraud or abuse prevention at scale
• Threat modeling for fraud and scam ecosystems, including social engineering, romance scams, investment fraud, impersonation, and phishing
• Identifying and articulating common fraud tactics (e.g., pig butchering, advance fee fraud, account takeover facilitation) and how they manifest on AI platforms
• Using SQL or other data analysis tools to identify trends, measure enforcement efficacy, and surface policy gaps
• Collaborating cross-functionally with Engineering, ML, Legal, and Policy teams on safety initiatives
• Working with generative AI products, including writing effective prompts for content review and enforcement use cases
• Thriving in a fast-paced, ambiguous environment where priorities shift and the threat landscape evolves rapidly

Preferred Qualifications: 

• Experience at a major technology platform, financial institution, or fraud intelligence firm in a policy, operations, or investigative capacity
• Familiarity with the generative AI risk landscape and how large language models can be exploited for fraud and social engineering
• Background in threat intelligence, financial crimes compliance (AML/KYC), or law enforcement focused on cyber-enabled fraud
• Demonstrated ability to develop and communicate policy positions to diverse stakeholders including legal counsel and executive leadership

About the role

As a Safeguards Policy Design Manager, you will be responsible for developing usage policies, clarifying enforcement guidelines, and advising on safety interventions for our products and services. Your core focus will be on age-appropriate design and experiences, including child safety, age assurance, content classification, and adult sexual content. You will help define best practices for developers building on claude for deployment to users across different developmental stages, design age-assurance policies that protect minors from inappropriate content and interactions, and establish clear boundaries for adult content and experiences. In addition, you will advise teams on opportunities for age-appropriate helpfulness, including advising cross-functional teams on beneficial use cases for younger users where appropriate. Safety is core to our mission and you’ll help shape policy creation and development so that our users can safely interact with and build on top of our products in a harmless, helpful and honest way.

*Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature.

Responsibilities:

• Serve as an internal subject matter expert, leveraging deep expertise in child safety, adult content, youth development, and age-appropriate design to:

  • Draft new policies that help govern the responsible use of our models for emerging capabilities and use cases

  • Design evaluation frameworks for testing model performance in areas of expertise

• Conduct regular reviews and testing of existing policies to identify and address gaps and ambiguities

• Review flagged content to drive enforcement and policy improvements

• Update our usage policies based on feedback collected from external experts, our enforcement team, and edge cases that you will review

• Work with safeguards product teams to identify and mitigate concerns, and collaborate on designing appropriate interventions for users across different age groups

• Advise on age assurance approaches and content classification frameworks in partnership with Enforcement, Product, Engineering, and Legal teams

• Educate and align internal stakeholders around our policies and our approach to safety in your focus area(s)

• Keep up to date with new and existing AI policy norms, regulatory requirements (e.g., age-appropriate design codes), and industry standards, and use these to inform our decision-making on policy areas

You may be a good fit if you have experience:

• As a researcher, subject matter expert, or trust & safety professional working in one or more of the following focus areas: child safety, youth online safety, age assurance, developmental science, content classification and rating systems, or adult content policy. Note: For this role, an advanced degree in developmental psychology, child development, education, or a related field is preferred.

• Drafting or updating product and / or user policies, with the ability to effectively bridge technical and policy discussions

• Designing or implementing age-appropriate experiences, age assurance mechanisms, or content classification / labeling systems

• Working with generative AI products, including writing effective prompts for policy evaluations and classifier development

• Aligning product policy decisions between diverse sets of stakeholders, such as Product, Engineering, Public Policy, and Legal teams

• Understanding the challenges that exist in developing and implementing product policies at scale, including in the content moderation space

• Thinking creatively about the risks and benefits of new technologies, and leveraging data and research to inform policy recommendations

• Navigating and prioritizing work efforts amidst ambiguity

About the role

As the Vendor and Contract Manager on the Safeguards team, you will own the end-to-end lifecycle of Anthropic's safety-critical vendor, partner, and consultant relationships — from identifying and selecting vendors through contract negotiation, onboarding, ongoing performance management, and renewal. The vendors and partners you'll manage span verification, threat intelligence, process outsourcing, capability evaluation, civil society consultation, and research collaboration.

You'll build repeatable processes where they're needed while staying nimble enough to handle novel partnership structures, like research collaborations, civil society consultations, and model red-teaming engagements that don't fit neatly into standard procurement workflows. You'll work closely with legal, procurement, finance, and engineering teams, and you'll be the person who knows where every Safeguards contract stands, what we're spending, and where we should consider a change.

This is a role for someone who's comfortable operating across commercial, legal, and technical contexts in a fast-moving environment — someone who can negotiate contract terms, work with legal teams to redline contracts,  set up model access for a research partner, and handle a vendor performance issue in one day.

*Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature.

Responsibilities:

Vendor Selection & Onboarding

• Understand the broad vendor landscape for Safeguards and drive vendor selection processes with expert input, factoring in tradeoffs between capability, price, and internal resources across categories including verification, threat intelligence, process outsourcing, and capability evaluation
• Conduct vendor due diligence and coordinate security and data governance reviews for vendors handling sensitive model access or content
• Forecast future partnership needs and proactively research vendors and partners that could meet emerging Safeguards requirements

Contract & Budget Management

• Manage contracts across the Safeguards vendor and partner portfolio, working with legal and procurement teams on contract redlining, negotiation, and execution
• Work with legal teams and potential research partners to develop novel agreements for research collaboration, civil society consultation, and model red-teaming
• Handle invoicing, payment, and renewal processes with partners
• Own Safeguards vendor budget tracking and planning in partnership with finance teams, maintaining a clear picture of current spend and forecasting future needs

Ongoing Vendor & Partner Management

• Manage vendor and researcher access to models and products during testing phases and trials
• Oversee and monitor vendor performance and usage, flagging issues and resolving concerns and disputes as they arise
• Report on vendor performance, spend, and contract status to Safeguards leadership

You may be a good fit if you have:

• 5+ years in vendor management, procurement, or contract operations, ideally in risk, fraud, compliance, or trust & safety contexts at a technology company
• Demonstrated experience reviewing and negotiating contracts, including comfort with redlining and working alongside legal counsel
• Track record managing vendor budgets, including forecasting, tracking spend, and making tradeoff recommendations
• Understanding of AI safety, account abuse, or platform integrity issues — you know what verification vendors, threat intelligence providers, and content screening tools actually do
• Experience onboarding vendors and standing up new vendor relationships from scratch, not just managing existing ones
• Strong cross-functional collaboration skills, particularly with legal, procurement, finance, and engineering teams
• Comfort with ambiguity and fast-moving environments — you've built or significantly improved vendor management processes, not just inherited them

Nice to have:

• Experience in AI safety or AI-adjacent vendor ecosystems
• Familiarity with procurement tools such as Ironclad or Zip

About the role

As a Safeguards Analyst focusing on human exploitation and abuse, you will be responsible for building and executing enforcement workflows that detect and mitigate the use of our products to facilitate human trafficking, sextortion, image-based sexual abuse, bullying, and harassment. As a member of the user well-being team, your initial focus will be on standing up detection, review, and escalation workflows for this domain — from tuning classifiers and curating evaluation datasets through to managing external partnerships and real-world harm escalation pathways. This position may later expand to include broader areas of user well-being enforcement. Safety is core to our mission, and you'll help shape policy enforcement so that our users can interact with and build on top of our products across all surfaces in a harmless, helpful, and honest way.

Important context

In this position, you may be exposed to and engage with explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature. There is also an on-call responsibility across the Policy and Enforcement teams.

Responsibilities:

• Design and architect automated enforcement systems and review workflows for human exploitation and abuse, ensuring they scale effectively while maintaining high accuracy

• Partner with Product, Engineering, and Data Science teams to build and tune detection signals for human trafficking, sextortion, and image-based sexual abuse, and to develop custom mitigations for these sensitive policy areas

• Curate policy violation examples, maintain golden evaluation datasets, and track enforcement actions across both consumer and API surfaces

• Conduct deep-dive investigations into suspected exploitation activity — using SQL and other data analysis tools to surface threat patterns and bad-actor behavior in large datasets — then produce clear, well-sourced intelligence reports that inform detection strategy and surface policy gaps to the Safeguards policy design team

• Study trends internally and in the broader ecosystem — including evolving trafficking and sextortion tactics — to anticipate how AI systems could be misused for exploitation as capabilities advance

• Review and investigate flagged content to drive enforcement decisions and policy improvements, exercising careful judgment on the line between permitted adult content and exploitative material

• Build and maintain relationships with external intelligence partners — including hotlines, NGOs, and industry hash-sharing consortia — to inform our approach and enable appropriate real-world escalation

You may be a good fit if you have:

Required

• 3+ years of experience in trust and safety, content moderation, counter-exploitation work, or a related field

• Subject matter expertise in one or more of: human trafficking, human exploitation and abuse, sextortion, image-based sexual abuse / non-consensual intimate imagery, or commercial sexual exploitation

• Experience building or operating detection and review workflows for sensitive content, at a platform, NGO, hotline, or similar organization

• Ability to use SQL, Python, and/or other data analysis tools to interact with large datasets and derive insights that support key decisions and recommendations

• Demonstrated ability to analyze complex situations and make well-reasoned decisions under pressure

• Sound judgment in distinguishing permitted content from exploitative content, and comfort working in areas where these lines require careful reasoning

• Strong attention to detail and ability to maintain accurate documentation

• Ability to collaborate with team members while navigating rapidly evolving priorities and workstreams

Preferred

• Familiarity with the NGO and industry ecosystem working on these harms (for example, Polaris Project, Thorn, NCMEC, IWF, StopNCII, or industry hash-sharing initiatives)

• Experience conducting open-source investigations or threat actor profiling in a trust & safety, intelligence, or law enforcement context

• Experience working with generative AI products, including writing effective prompts for content review and enforcement

• A deep interest in AI safety and responsible technology development

• Experience standing up real-world harm escalation pathways or working with law enforcement referral processes

About the role

As a Research Lead on the Training Insights team, you'll develop the strategy for, and lead execution on, how we measure and characterize model capabilities across training and deployment. This is a hands-on leadership role: you'll drive original research into new evaluation methodologies while leading a small team of researchers and research engineers doing the same.

Your work will span the full lifecycle of model development. You'll research and build new long-horizon evaluations that test the boundaries of what our models can achieve, develop novel approaches to measuring emerging capabilities, and deepen our understanding of how those capabilities develop — both during production RL training and after. You'll also take a cross-organizational view, working across Reinforcement Learning, Pretraining, Inference, Product, Alignment, Safeguards, and other teams to map the landscape of model evaluations at Anthropic and identify critical gaps in coverage.

This role carries significant visibility and impact. You'll help shape the evaluation narrative for model releases, contributing directly to how Anthropic communicates about its models to both internal and external audiences. Done well, you will change how the industry measures and understands model capabilities, significantly furthering our safety mission.  

Responsibilities: 

• Build new novel and long-horizon evaluations
• Develop novel measurement approaches for understanding how model capabilities emerge and evolve during RL training
• Lead strategic evaluation coverage across the company
• Shape the evaluation narrative for model releases
• Lead and mentor a small team of researchers and research engineers, setting research direction and fostering a culture of rigorous, creative research
• Design evaluation frameworks that balance scientific rigor with the practical demands of production training schedules
• Build and maintain relationships across Anthropic's research organization to ensure evaluation insights inform training and deployment decisions
• Contribute to the broader research community through publications, open-source contributions, or external engagement on evaluation best practices

You may be a good fit if you: 

• Have significant experience designing and running evaluations for large language models or similar complex ML systems
• Have led technical projects or teams, either formally or through sustained ownership of critical research directions
• Are equally comfortable designing experiments and writing code—you can move between research and implementation fluidly
• Think strategically about what to measure and why, not just how to measure it
• Can synthesize information across multiple teams and workstreams to form a coherent picture of model capabilities
• Communicate complex technical findings clearly to both technical and non-technical audiences
• Are results-oriented and thrive in fast-paced environments where priorities shift based on research findings
• Care deeply about AI safety and want your work to directly influence how capable AI systems are developed and deployed

Strong candidates may also have: 

• Experience building evaluations for long-horizon or agentic tasks
• Deep familiarity with Reinforcement Learning training dynamics and how model behavior changes during training
• Published research in machine learning evaluation, benchmarking, or related areas
• Experience with safety evaluation frameworks and red teaming methodologies
• Background in psychometrics, experimental psychology, or other measurement-focused disciplines
• A track record of communicating evaluation results to inform high-stakes decisions about model development or deployment
• Experience managing or mentoring researchers and engineers

Representative projects: 

• Designing and implementing a suite of long-horizon evaluations that test model capabilities on tasks requiring sustained reasoning, planning, and tool use over extended interactions
• Building systems to track capability development across RL training checkpoints, surfacing insights about when and how specific capabilities emerge
• Conducting a cross-org audit of evaluation coverage, identifying blind spots, and prioritizing new evaluations to fill critical gaps across Pretraining, RL, Inference, and Product
• Developing the evaluation methodology and narrative for a major model release, working with research leads and communications to clearly characterize model capabilities and limitations
• Researching and prototyping novel evaluation approaches for capabilities that are difficult to measure with existing benchmarks
• Leading a team effort to build reusable evaluation infrastructure that serves multiple teams across the research organization

About the Role

We are looking for a Technical CBRN-E Threat Investigator to join our Threat Intelligence team. In this role, you will be responsible for detecting, investigating, and disrupting the misuse of Anthropic's AI systems for Chemical, Biological, Radiological, Nuclear, and Explosives (CBRN-E) threats. We are particularly interested in candidates with deep expertise in either chemical defense or biodefense.

You will work at the intersection of AI safety and CBRN security, conducting thorough investigations into potential misuse cases, developing novel detection techniques, and building robust defenses against threat actors who may attempt to leverage our AI technology for developing weapons, synthesizing dangerous compounds, or creating biological harm. Your specialized domain expertise will be critical to protecting against some of the most serious potential misuses of AI systems.

Important context: In this position you may be exposed to explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature. This role may require responding to escalations during weekends and holidays.

Responsibilities

• Detect and investigate attempts to misuse Anthropic's AI systems for developing, enhancing, or disseminating CBRN-E weapons, pathogens, toxins, or other threats to harm people, critical infrastructure, or the environment
• Conduct technical investigations using SQL, Python, and other tools to analyze large datasets, trace user behavior patterns, and uncover sophisticated CBRN-E threat actors
• Develop CBRN-E-specific detection capabilities, including abuse signals, tracking strategies, and detection methodologies tailored to dual-use research concerns
• Create actionable intelligence reports on CBRN-E attack vectors, vulnerabilities, and threat actor TTPs leveraging AI systems
• Conduct cross-platform threat analysis grounded in real threat actor behavior, open-source research, and publicly reported programs
• Collaborate with policy and enforcement teams to make informed decisions about user violations and ensure appropriate mitigation actions
• Engage with external stakeholders including government agencies, regulatory bodies, scientific organizations, and biosecurity/chemical security research communities
• Inform safety-by-design strategies by forecasting how threat actors may leverage advances in AI technology for CBRN-E purposes

You may be a good fit if you

• Have deep domain expertise in biosecurity, chemical defense, biological weapons non-proliferation, dual-use research of concern (DURC), synthetic biology, or related CBRN-E threat domains
• Have demonstrated proficiency in SQL and Python for data analysis and threat detection
• Have experience with threat actor profiling and utilizing threat intelligence frameworks
• Have hands-on experience with large language models and understanding of how AI technology could be misused for CBRN-E threats
• Have excellent stakeholder management skills and ability to work with diverse teams including researchers, policy experts, legal teams, and external partners
• Can present analytical work to both technical and non-technical audiences, including government stakeholders and senior leadership

Strong candidates may also have

• Advanced degree (MS or PhD) in biological sciences, chemistry, biodefense, biosecurity, or related field
• Real-world experience countering weapons of mass destruction or other high-risk asymmetric threats
• Experience working with government agencies or in regulated environments dealing with sensitive CBRN-E information
• Background in AI safety, machine learning security, or technology abuse investigation
• Familiarity with synthetic biology, biotechnology, or dual-use research
• Experience building and scaling threat detection systems or abuse monitoring programs
• Active Top Secret security clearance

About the Role:

We are looking for a cybersecurity expert to lead our efforts to prevent AI misuse in the cyber domain. As a Cyber Harms Technical Policy Manager, you will lead a team applying deep technical expertise to inform the design of safety systems that detect harmful cyber behaviors and prevent misuse by sophisticated threat actors. Working closely with Research Engineers who build these safety systems, you and your team will provide the critical cybersecurity domain knowledge needed to ensure our safeguards are effective against real-world threats. You will be at the forefront of defining what responsible AI safety looks like in the cybersecurity domain, working across research, policy, and engineering to translate complex cyber threat concepts into concrete technical safeguards and actionable policies. This is a unique opportunity to shape how frontier AI models handle dual-use cybersecurity knowledge—balancing the tremendous potential of AI to advance legitimate security research and defensive capabilities while preventing misuse by malicious actors.

In this role, you will:

• Lead and grow a team of technical specialists focused on cyber threat modeling and evaluation frameworks
• Design and oversee execution of capability evaluations ("evals") to assess the cyber-relevant capabilities of new models
• Create comprehensive cyber threat models, including attack vectors, exploit chains, precursor identification, and weaponization techniques
• Develop and iterate on usage policies that govern responsible use of our models for emerging capabilities and use cases related to cyber harms
• Serve as the primary domain expert on cyber harms, advising cross-functional teams on threat landscapes and mitigation strategies
• Collaborate closely with internal and external threat modeling experts to develop training data for safety systems, and with ML engineers to train these systems, optimizing for both robustness against adversarial attacks and low false-positive rates for legitimate security researchers
• Analyze safety system performance in traffic, identifying gaps and proposing improvements
• Conduct regular reviews of existing policies and enforcement systems to identify and address gaps and ambiguities related to cybersecurity risks
• Develop rigorous stress-testing of safeguards against evolving cyber threats and product surfaces
• Partner with Research, Product, Policy, Security Team, and Frontier Red Team to ensure cybersecurity safety is embedded throughout the model development lifecycle
• Translate cybersecurity domain knowledge into actionable safety requirements and clearly articulated policies
• Contribute to external communications, including model cards, blog posts, and policy documents related to cybersecurity safety
• Monitor emerging technologies and threat landscapes for their potential to contribute to new risks and mitigation strategies, and strategically address these
• Mentor and develop team members, fostering a culture of technical excellence and responsible AI development

You may be a good fit if you have:

• An M.S. or PhD in Computer Science, Cybersecurity, or a related technical field, OR equivalent professional experience in offensive or defensive cybersecurity
• 5+ years of hands-on experience in cybersecurity, with deep expertise in areas such as vulnerability research, exploit development, network security, malware analysis, or penetration testing
• 2+ years of experience managing technical teams or leading complex technical projects with multiple stakeholders
• Experience in scientific computing and data analysis, with proficiency in programming (Python preferred)
• Deep expertise in modern cybersecurity, including both offensive techniques (vulnerability research, exploit development, penetration testing, malware analysis) and defensive measures (detection, monitoring, incident response)
• Demonstrated ability to create threat models and translate technical cyber risks into policy frameworks
• Familiarity with responsible disclosure practices, vulnerability coordination, and cybersecurity frameworks (e.g., MITRE ATT&CK, NIST Cybersecurity Framework, CWE/CVE systems)
• Strong analytical and writing skills, with the ability to navigate ambiguity and explain complex technical concepts to non-technical stakeholders
• Experience developing policies or guidelines at scale, balancing safety concerns with enabling legitimate use cases
• A passion for learning new skills and an ability to rapidly adapt to changing techniques and technologies
• Comfort working in a fast-paced environment where priorities may shift as AI capabilities evolve
• Track record of translating specialized technical knowledge into actionable safety policies or enforcement guidelines

Preferred Qualifications:

• Background in AI/ML systems, particularly experience with large language models
• Experience developing ML-based security systems or adversarial ML research
• Experience working with defense, intelligence, or security organizations (e.g., NSA, CISA, national labs, security contractors)
• Published security research, disclosed vulnerabilities, or participated in bug bounty programs
• Understanding of Trust & Safety operations and content moderation at scale
• Certifications such as OSCP, OSCE, GXPN, or equivalent demonstrating technical depth
• Understanding of dual-use security research concerns and ethical considerations in AI safety

About the Team

The Universes team within Research is responsible for training AI models to perform complex, difficult, long-horizon agentic tasks in ultra-realistic settings. We design and implement novel training environments that go far beyond what models can do today — environments where models learn to navigate ambiguity, handle interruptions, maintain context over extended interactions, and exercise judgment in open-ended scenarios.

About the Role

We're looking for Research Engineers to help us build the next generation of training environments for capable and safe agentic AI.

This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to research direction. You'll work on fundamental research in reinforcement learning, designing training environments and methodologies that push the state of the art, and building evaluations that measure genuine capability.

Responsibilities:

• Build the next generation of agentic environments

• Build rigorous evaluations that measure real capability

• Collaborate across research and infrastructure teams to ship environments into production training

• Debug and iterate rapidly across research and production ML stacks

• Contribute to research culture through technical discussions and collaborative problem-solving

You may be a good fit if you:

• Are highly impact-driven — you care about outcomes, not activity

• Operate with high agency

• Have good research taste or senior technical experience, demonstrating good judgment in identifying what actually matters in complex problem spaces

• Can balance research exploration with engineering implementation

• Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems

• Are comfortable with uncertainty and adapt quickly as the landscape shifts

• Have strong software engineering skills and can build robust infrastructure

• Enjoy pair programming (we love to pair!)

Strong candidates may also have one or more of the following:

• Have industry experience with large language model training, fine-tuning or evaluation

• Have industry experience building RL environments, simulation systems, or large-scale ML infrastructure

• Senior experience in a relevant technical field even if transitioning domains

• Deep expertise in sandboxing, containerization, VM infrastructure, or distributed systems

• Published influential work in relevant ML areas

About the Role

We are looking for a Technical Cyber Threat Investigator to join our Threat Intelligence team. In this role, you will be responsible for detecting, investigating, and disrupting the misuse of Anthropic's AI systems for malicious cyber operations. 

You will work at the intersection of AI safety and cybersecurity, conducting thorough investigations into potential misuse cases, developing novel detection techniques, and building robust defenses against emerging cyber threats in the rapidly evolving landscape of AI-enabled risks. Your work will directly protect the broader ecosystem from sophisticated threat actors who seek to leverage AI technology for harm.

Important context: In this position you may be exposed to explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature. This role may require responding to escalations during weekends and holidays.

Responsibilities

• Detect and investigate attempts to misuse Anthropic's AI systems for cyber operations, including influence operations, malware development, social engineering, and other adversarial activities
• Develop abuse signals and tracking strategies to proactively detect sophisticated threat actors across our platform
• Create actionable intelligence reports on new attack vectors, vulnerabilities, and threat actor TTPs targeting LLM systems
• Conduct cross-platform threat analysis grounded in real threat actor behavior, using open-source research, dark web monitoring, and internal data
• Utilize investigation findings to implement systematic improvements to our safety approach and mitigate harm at scale
• Study trends internally and in the broader ecosystem to anticipate how AI systems could be misused, generating and publishing reports
• Build and maintain relationships with external threat intelligence partners, information sharing communities, and government stakeholders
• Work cross-functionally to build out our threat intelligence program, establishing processes, tools, and best practices

You may be a good fit if you

• Have demonstrated proficiency in SQL and Python for data analysis and threat detection
• Have experience with large language models and understanding of how AI technology could be misused for cyber threats
• Have subject matter expertise in abusive user behavior detection, such as influence operations, coordinated inauthentic behavior, or cyber threat intelligence
• Have experience tracking threat actors across surface, deep, and dark web environments
• Can derive insights from large datasets to make key decisions and recommendations
• Have experience with threat actor profiling and utilizing threat intelligence frameworks (MITRE ATT&CK, etc.)
• Have strong project management skills and ability to build processes from the ground up
• Possess excellent communication skills to collaborate with cross-functional teams and present to leadership

Strong candidates may also have

• Experience working with government agencies or in regulated environments
• Background in AI safety, machine learning security, or technology abuse investigation
• Experience building and scaling threat detection systems or abuse monitoring programs
• Active Top Secret security clearance

Deadline to apply

None. Applications will be reviewed on a rolling basis.

About the role

You will deeply understand the research workflows of our Finetuning teams and automate the high-friction parts – turning days of manual experimentation into hours. You’ll build the tools and infrastructure that enable researchers across the organization to develop, evaluate, and optimize reward signals for training our models. Your scalable platforms will make it easy to experiment with different reward methodologies, assess their robustness, and iterate rapidly on improvements to help the rest of Anthropic train our reward models.

This is a role for someone who wants to stay close to the science while having outsized leverage. You'll partner directly with researchers on the Rewards team and across the broader Fine-Tuning organization to understand what slows them down: running human data experiments before adding to preference models, debugging reward hacks, comparing rubric methodologies across domains. Then you'll build the systems that make those workflows 10x faster. When you have bandwidth, you'll contribute directly to research projects yourself. Your work will directly impact our ability to scale reward development across domains, from crafting and evaluating rubrics to understanding the effects of human feedback data to detecting and mitigating reward hacks. 

We're looking for someone who combines strong engineering fundamentals with research experience – someone who can scope ambiguous problems, ship quickly, and cares as much about the science as the systems.

Note: For this role, we conduct all interviews in Python.

Responsibilities

• Design and build infrastructure that enables researchers to rapidly iterate on reward signals, including tools for rubric development, human feedback data analysis, and reward robustness evaluation
• Develop systems for automated quality assessment of rewards, including detection of reward hacks and other pathologies
• Create tooling that allows researchers to easily compare different reward methodologies (preference models, rubrics, programmatic rewards) and understand their effects
• Build pipelines and workflows that reduce toil in reward development, from dataset preparation to evaluation to deployment
• Implement monitoring and observability systems to track reward signal quality and surface issues during training runs
• Collaborate with researchers to translate science requirements into platform capabilities
• Optimize existing systems for performance, reliability, and ease of use
• Contribute to the development of best practices and documentation for reward development workflows

You may be a good fit if you

• Have prior research experience 
• Are excited to work closely with researchers and translate ambiguous requirements into well-scoped engineering projects
• Have strong Python skills
• Have experience with ML workflows and data pipelines, and building related infrastructure/tooling/platforms
• Are comfortable working across the stack, ranging from data pipelines to experiment tracking to user-facing tooling
• Can balance building robust, maintainable systems with the need to move quickly in a research environment
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Care about the societal impacts of your work and are motivated by Anthropic's mission to develop safe AI

Strong candidates may also have experience with

• Experience with ML research
• Building internal tooling and platforms for ML researchers
• Data quality assessment and pipeline optimization
• Experiment tracking, evaluation frameworks, or MLOps tooling
• Large-scale data processing (e.g., Spark, Hive, or similar)
• Kubernetes, distributed systems, or cloud infrastructure
• Familiarity with reinforcement learning or fine-tuning workflows 

Representative projects

• Building infrastructure that allows researchers to rapidly test new rubric designs against small models before scaling up
• Developing automated systems to detect reward hacks and surface problematic behaviors during training
• Creating tooling for comparing different grading methodologies and understanding their effects on model behavior
• Building a data quality flywheel that helps researchers identify problematic transcripts and feed improvements back into the system
• Developing dashboards and monitoring systems that give researchers visibility into reward signal quality across training runs
• Streamlining dataset preparation workflows to reduce latency and operational overhead

About the role

As a Senior Research Scientist on our Reward Models team, you'll lead research efforts to improve how we specify and learn human preferences at scale. Your work will directly shape how our models understand and optimize for what humans actually want — enabling Claude to be more useful, more reliable, and better aligned with human values.

This role focuses on pushing the frontier of reward modeling for large language models. You'll develop novel architectures and training methodologies for RLHF, research new approaches to LLM-based evaluation and grading (including rubric-based methods), and investigate techniques to identify and mitigate reward hacking. You'll collaborate closely with teams across Anthropic, including Finetuning, Alignment Science, and our broader research organization, to ensure your work translates into concrete improvements in both model capabilities and safety. 

We're looking for someone who can drive ambitious research agendas while also shipping practical improvements to production systems. You'll have the opportunity to work on some of the most important open problems in AI alignment, with access to frontier models and significant computational resources. Your work will directly advance the science of how we train AI systems to be both highly capable and safe. 

Note: For this role, we conduct all interviews in Python.

Responsibilities

• Lead research on novel reward model architectures and training approaches for RLHF
• Develop and evaluate LLM-based grading and evaluation methods, including rubric-driven approaches that improve consistency and interpretability
• Research techniques to detect, characterize, and mitigate reward hacking and specification gaming
• Design experiments to understand reward model generalization, robustness, and failure modes
• Collaborate with the Finetuning team to translate research insights into improvements for production training pipelines
• Contribute to research publications, blog posts, and internal documentation
• Mentor other researchers and help build institutional knowledge around reward modeling

You may be a good fit if you

• Have a track record of research contributions in reward modeling, RLHF, or closely related areas of machine learning
• Have experience training and evaluating reward models for large language models
• Are comfortable designing and running large-scale experiments with significant computational resources
• Can work effectively across research and engineering, iterating quickly while maintaining scientific rigor
• Enjoy collaborative research and can communicate complex ideas clearly to diverse audiences
• Care deeply about building AI systems that are both highly capable and safe

Strong candidates may also

• Have published research on reward modeling, preference learning, or RLHF
• Have experience with LLM-as-judge approaches, including calibration and reliability challenges
• Have worked on reward hacking, specification gaming, or related robustness problems
• Have experience with constitutional AI, debate, or other scalable oversight approaches
• Have contributed to production ML systems at scale
• Have familiarity with interpretability techniques as applied to understanding reward model behavior

About the role

The Environment Scaling team is a team of researchers and engineers whose goal is to improve the intelligence of our public models for novel verticals and use cases. The team builds the training environments that fuel RL at scale. This is a unique role that combines executing directly on ML research, data operations, and project management to improve our models. You'll own the end-to-end process of creating RL environments for new capabilities: identifying high-value tasks, designing reward signals, managing vendor relationships, and measuring impact on model performance.

Responsibilities:

• Improve and execute our fine-tuning strategies for adapting Claude to new domains and tasks
• Manage technical relationships with external data vendors, including evaluation of data quality and reward design
• Collaborate with domain experts to design data pipelines and evaluations
• Explore novel ways of creating RL environments for high value tasks
• Develop and improve QA frameworks to catch reward hacking and ensure environment quality
• Partner with other RL research teams and product teams to translate capability goals into training environments and evals

You may be a good fit if you:

• Have experience with fine-tuning large language models for specific domains or real-world use cases and/or domain expertise in an area where we would like to make our models more useful.
• Have experience with reinforcement learning, reward design, or training data curation for LLMs
• Are comfortable managing technical vendor relationships and iterating quickly on feedback
• Find value in reading through datasets to understand them and spot issues
• Have strong project management and interpersonal skills
• Are passionate about making AI more useful and accessible across different industries
• Are excited about a role that includes a combination of ML research, data operations, and project management

Strong candidates may also:

• Have experience training production ML systems
• Be familiar with distributed systems and cloud infrastructure
• Have domain expertise in an area where we would like to make our models more useful
• Have experience working with external vendors or technical partners

About the Role

Anthropic's Safeguards team is responsible for enforcing our policies, protecting users, and ensuring our platform is not misused. As a Safeguards Enforcement Analyst focused on Safety Evaluations, you'll play a central role in ensuring our models meet safety and policy standards before and after launch. You'll run and monitor evaluations, drive mitigations when issues surface, coordinate the creation of new evals, and help build the processes and documentation that allow the team to scale this work over time.

This role requires someone who is detail-oriented, comfortable navigating ambiguity, and capable of coordinating across teams to break new ground and drive work to completion. This work is deeply cross-functional — you'll partner closely with policy experts, Safeguards engineering teams, and many other stakeholders throughout the organization to ensure our evaluations are comprehensive and current, and that findings translate into meaningful improvements to model behavior.

Responsibilities

• Support model launch readiness by running evaluations, monitoring and interpreting results, and surfacing regressions or unexpected behavior changes to relevant stakeholders
• Partner closely with policy and domain experts throughout the evaluation lifecycle — from identifying risks and scoping the right evaluation approach, to coordinating creation of new evals and ensuring existing ones remain current with evolving policies, threat vectors, and model capabilities
• Work with cross-functional stakeholders to help manage evaluation outcomes, including interpreting results and driving mitigations where needed
• Think strategically about eval quality to build processes and eval paradigms that keep evaluations unsaturated, high-signal, and insightful as models improve
• Build out processes and frameworks for creating product-specific evaluations as Anthropic's product surface area expands
• Help design and scope tooling improvements that accommodate evolving eval needs and expand self-serve eval creation and iteration for non-technical users
• Write and maintain rigorous documentation for evaluation creation, execution, and interpretation as the team builds out eval tooling and processes

You may be a good fit if you:

• Have experience in trust and safety, content operations, policy enforcement, or a related operational role at a technology company
• Thrive in ambiguous, fast-moving environments — you're energized rather than frustrated when the path forward isn't clearly defined and you need to figure it out as you go
• Have experience building processes, workflows, or programs from scratch (zero-to-one work), not just maintaining existing ones
• Have strong program management instincts, naturally creating structure around complex, multi-stakeholder efforts by tracking timelines, dependencies, and deliverables to keep work on track
• Are eager to expand your technical toolkit, including adopting internal tools and AI-assisted workflows (e.g., Claude Code) to accelerate your work
• Can manage multiple concurrent workstreams across different domain areas without losing track of details — strong prioritization and context-switching are essential when deadlines and priorities shift quickly
• Are a strong generalist comfortable moving fluidly across different types of work and switching contexts throughout the day
• Are comfortable making judgment calls with incomplete information and escalating appropriately when needed
• Communicate clearly and concisely, both in writing and cross-functionally

Strong candidates may also have:

• Experience operating under tight, high-stakes timelines — such as product launch cycles, incident response, or regulatory deadlines — where information and priorities can shift with little notice
• Experience coordinating across engineering, policy, and product teams to translate findings into concrete action
• Experience building and maintaining SOPs, runbooks, and operational documentation in fast-changing environments
• Proficiency with data tools (SQL, dashboards, spreadsheets) sufficient to maintain and improve workflows
• Comfort working with sensitive content areas as part of eval creation or enforcement review responsibilities

About the Role

As a TPU Kernel Engineer, you'll be responsible for identifying and addressing performance issues across many different ML systems, including research, training, and inference. A significant portion of this work will involve designing and optimizing kernels for the TPU. You will also provide feedback to researchers about how model changes impact performance. Strong candidates will have a track record of solving large-scale systems problems and low-level optimization.

You may be a good fit if you:

• Have significant experience optimizing ML systems for TPUs, GPUs, or other accelerators
• 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
• Designing and implementing kernels for TPUs or other ML accelerators
• Understanding accelerators at a deep level, e.g. a background in computer architecture
• ML framework internals
• Language modeling with transformers

Representative projects:

• Implement low-latency, high-throughput sampling for large language models
• Adapt existing models for low-precision inference
• Build quantitative models of system performance
• Design and implement custom collective communication algorithms
• Debug kernel performance at the assembly level

About the Role

Anthropic is making significant, sustained investment in compute infrastructure to support our AI safety mission. We are looking for an Infrastructure Tax Lead to own tax end-to-end across that portfolio — sitting at the point of deal flow, embedded with the Infrastructure team, and coordinating across Legal, Technical Accounting, FP&A, International Tax, Transfer Pricing, Provision, and Incentives.

Responsibilities

• Serve as the embedded tax partner to Infrastructure team on deal intake: gather facts on site specs, counterparty structure, commercial terms, and timing; provide structure review and term-sheet input early enough to shape the deal 
• Lead Incentives workstream on state and local incentives, sales and use exemptions, and site selection tax input; ensure incentive commitments and compliance obligations are reflected in the integrated tax position for each site
• Partner with Tax Transactions and Tax Planning teams  on lease characterization, entity structure, and contract tax provisions; own the tax read on lease-versus-purchase, and treatment across a portfolio of non-standard structures
• Lead after-tax deal economics: bonus depreciation modeling on large-scale buildouts, NOL utilization, and scenario analysis; partner with Tax Planning and FP&A to ensure tax assumptions are reflected accurately in deal approval packages
• Coordinate with Technical Accounting on lease-versus-purchase treatment, consolidation questions, capitalization policy, and book-tax differences across a range of deal structures
• Stand up and maintain datacenter entity structures across jurisdictions: entity formation, operationalization with local teams, contemporaneous documentation, withholding on cross-border financing, permanent establishment risk, and debt-versus-equity characterization
• Partner with transfer pricing on policy for the infrastructure footprint: intercompany compute pricing, benchmarking, and documentation that will withstand scrutiny as intercompany flows scale
• Partner with the tax provision team on quarterly impact of new structures and deferred tax positions; ensure there are no surprises between deal close and quarter close
• Build and maintain infrastructure tax playbooks, issue-spotting checklists, and internal processes so the function scales with deal volume rather than linearly with headcount

You may be a good fit if you have

• 12+ years of tax experience with significant exposure to datacenter, REIT, or large-scale real estate tax planning, including meaningful international range
• JD or CPA required; LL.M. in Taxation or MST a plus
• Deep technical command of lease characterization and Section 467, bonus depreciation modeling on capital-intensive buildouts.
• Experience standing up and maintaining entity structures across multiple jurisdictions, including contemporaneous documentation and operationalizing with local finance, legal, and accounting teams
• Working fluency in cross-border withholding on intercompany and third-party financing, permanent establishment analysis, and debt-versus-equity characterization
• Track record of owning the integrated tax position across a portfolio of deals — not advising on one issue at a time, but carrying the thread across functions from term sheet to post-close
• Demonstrated ability to operate as a cross-functional coordinator: comfortable running point across Legal, Accounting, FP&A, and business teams without formal authority over any of them
• Exceptional written and verbal communication — able to translate complex tax positions into clear guidance for Infrastructure leadership and deal teams
• Comfort with ambiguity and a track record of building processes from scratch in a fast-moving environment

Strong candidates may also have

• Big 4 or law firm experience in a datacenter, REIT, or infrastructure tax practice
• In-house tax experience at a hyperscaler, cloud provider, or large-scale datacenter operator
• Hands-on transfer pricing experience for intercompany services or compute, including benchmarking and documentation
• Experience with the owner-operator transition: construction-period capitalization, placed-in-service timing disputes, property tax during buildout, and sales/use on construction inputs versus operating equipment
• Background in state and local incentives, economic development negotiation, or site selection tax — either as a dedicated practitioner or as a frequent collaborator
• Experience with non-US datacenter tax regimes and cross-border infrastructure structures
• Existing relationships with datacenter developers, REIT tax counsel, or Big 4 infrastructure tax teams

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. 

About the Team

Anthropic’s Infrastructure team is responsible for designing, delivering, and scaling the physical compute environments that power our AI research and products. The team sits at the intersection of internal customers and an ecosystem of external engineering, construction, and development partners. From site selection through design, construction, commissioning, and ongoing operations, Infrastructure ensures that Anthropic’s datacenter footprint keeps pace with our research ambitions.

About the Role

We are looking for a Design Execution Manager to own the bridge between Anthropic’s technical requirements and the third-party partners who bring our datacenters to life. This is not a pure design role or a pure project management role—it lives in the critical space between the two, ensuring that design follows the requirements, and that technical intent survives every handoff from concept through turnover.

Scope spans the full design lifecycle: concept, schematic, permitting, development, construction administration, commissioning, and operations. The right candidate thrives in environments where nimble but structured processes need to be built, not just followed, and is energized by the challenge of standing up execution frameworks across a rapidly growing portfolio of mission-critical facilities.

Responsibilities

Design Execution & Partner Oversight

• Drive execution of Anthropic’s technical requirements for third-party datacenter delivery partners, ensuring design intent is consistently translated from BOD through construction documents.

• Define the design execution framework—deliverable requirements, review gates, and quality standards—for each partner engagement.

• Drive accountability for partner deliverable quality across milestones, evaluating deliverables for cross-discipline consistency and alignment to Anthropic’s requirements.

• Partner with external design teams and stakeholders to execute design document development and issuance across all project phases.

Change Management & Technical Continuity

• Own the design change management process across projects, ensuring technical decisions are documented, resolved, and implemented through construction.

• Review and develop responses to contractor RFIs, maintaining design intent while accommodating field conditions.

• Own technical continuity across design, construction, commissioning, and turnover, driving alignment between internal leads on phase transition standards and acceptance criteria.

• Support project closeout and as-built documentation processes.

Constructability & Risk Management

• Facilitate constructability review processes between design and construction teams, identifying integration risks and maintaining alignment between design intent and field execution as conditions evolve.

• Identify and mitigate design risks; ensure robust QA/QC practices across the design and construction lifecycle.

• Perform project site reviews and deliver technical reports on design compliance and construction progress.

Cross-Functional Coordination

• Interface with internal stakeholders—construction execution, supply chain, facilities operations, and security—to align design solutions with technical and business objectives.

• Partner with internal teams to define infrastructure requirements and translate them into actionable design criteria for external partners.

• Identify and implement opportunities for process improvements, design optimization, and schedule/performance/cost tradeoffs.

• Review commissioning scripts and final reports to validate performance and functionality against Anthropic’s standards.

Qualifications 

Required

• 10+ years in datacenter or mission-critical infrastructure delivery, spanning design and delivery phases.

• Direct experience in owner’s engineer or technical oversight roles—not purely design production or purely project management.

• Working knowledge of mechanical, electrical, and cooling systems in datacenter environments.

• Experience managing design change processes, RFIs, and construction documentation workflows.

• Track record of coordinating across multiple disciplines and organizations on complex infrastructure projects.

• Deep knowledge of industry standards, building codes, and safety standards applicable to mission-critical facilities.

• Comfortable operating with authority in ambiguous environments where processes need to be built, not just followed.

• BS in Mechanical Engineering, Electrical Engineering, Architecture, or related field.

Preferred

• Professional Engineer (PE) or Registered Architect (RA) license.

• Experience stamping construction drawing packages.

• Proficiency with Revit/BIM, Autodesk, or similar design software applications.

• Experience integrating sustainability, energy efficiency, and resiliency goals into datacenter system designs.

• Direct experience with large-scale AI/HPC infrastructure, including high-density cooling systems and power distribution at 50+ MW scale.

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

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

About the Role

Anthropic's AI infrastructure operates at massive scale, and extracting maximum compute throughput from every watt is a first-order priority. As a Power & Resource Efficiency Engineer, you'll sit at the intersection of IT and facilities — building the systems, models, and control loops that optimize how we allocate and consume power, cooling, and physical capacity across our TPU/GPU fleet. You'll own the technical strategy for turning raw data center capacity into reliable, efficient compute, working across power topology, workload scheduling, and real-time telemetry to push utilization as close to the physical envelope as possible while maintaining our availability commitments.

What You'll Do

• Build models that forecast consumption across electrical and mechanical subsystems, informing capacity planning, energy procurement, oversubscription targets and risks, including statistical modeling of cluster utilization, workload profiles, and failure modes.

• Design IT/OT interfaces that bridge compute orchestration with facility controls, enabling real-time telemetry across accelerator hardware, power distribution, cooling, and schedulers.

• Build and operate load management systems that use power and cooling topology to enable load management and power/thermal-aware placement to maximize throughput while meeting SLOs.

• Partner with data center providers to drive design optimizations and hold them accountable to SLA-grade performance standards, providing technical diligence on partner architectures.

What We're Looking For

• Deep knowledge of data center power distribution and cooling architectures, and how they interact with IT load profiles. Experience with reliability engineering, SLA development, and failure-mode analysis.

• Proficiency in statistical modeling and simulation for infrastructure capacity or power utilization. 

• Familiarity with SCADA/BMS/EPMS, telemetry pipelines, and control systems. Experience building software that bridges IT and OT.

• Exposure to accelerator deployments and their power management interfaces strongly preferred. 

• Demand response, grid interaction, or behind-the-meter generation experience is a plus.

• Ability to translate between infrastructure engineering, software teams, and external partners.

Required Qualifications

• Bachelor's degree in Electrical Engineering, Mechanical Engineering, Power Systems, Controls Engineering, or a related field

• 5+ years of experience in data center infrastructure or facility engineering

• Demonstrated experience with data center power distribution and cooling system architectures

• Experience building or operating software-based power management, load scheduling, or control systems

• Proficiency in Python or similar languages for statistical modeling, simulation, or automation of data center infrastructure optimizations 

• Familiarity with SCADA, BMS, EPMS, or industrial control systems and associated protocols (Modbus, BACnet, SNMP)

• Track record of cross-functional collaboration across hardware, software, and facilities teams

Preferred Qualifications

• Master's or PhD in Controls, Power Systems, or related discipline and 3+ years of experience in data center infrastructure or facility engineering

• Experience with accelerator-class deployments and their power management interfaces 

• Background in control theory, dynamical systems, or cyber-physical systems design

• Experience with energy storage, microgrid integration, demand response, or behind-the-meter generation

• Familiarity with reliability engineering methods 

• Experience with SLA development, availability modeling, or service credit frameworks

• Exposure to ML/optimization techniques applied to infrastructure or energy systems