Research Engineer, Performance RL (Reinforcement Learning)

About the role

We're hiring for the Code RL team within the RL organization. As a Research Engineer, you'll advance our models' ability to safely write correct, fast code for accelerators. You'll Need To Know Accelerator Performance Well To Turn It Into Tasks And Signals Models Can Learn From. Specifically, You Will Invent, design and implement RL environments and evaluations. Conduct experiments and shape our research roadmap. Deliver your work into training runs. Collaborate with other researchers, engineers, and performance engineering specialists across and outside Anthropic.

Responsibilities

• Invent, design and implement RL environments and evaluations.
• Conduct experiments and shape our research roadmap.
• Deliver your work into training runs.
• Collaborate with other researchers, engineers, and performance engineering specialists across and outside Anthropic.

Requirements

• Expertise with accelerators (CUDA, ROCm, Triton, Pallas).
• ML framework programming (JAX or PyTorch).
• Work across the stack – kernels, model code, distributed systems.
• Balance research exploration with engineering implementation.
• Passionate about AI's potential and committed to developing safe and beneficial systems.
• Strong candidates may also have experience with reinforcement learning.
• Experience porting ML workloads between different types of accelerators.
• Familiarity with LLM training methodologies.

Qualifications

• Years of experience required will correlate with the internal job level requirements for the position.

Skills

• Expertise with accelerators (CUDA, ROCm, Triton, Pallas).
• ML framework programming (JAX or PyTorch).
• Work across the stack – kernels, model code, distributed systems.
• Balance research exploration with engineering implementation.
• Passionate about AI's potential and committed to developing safe and beneficial systems.
• Experience porting ML workloads between different types of accelerators.
• Familiarity with LLM training methodologies.

Benefits

• Annual compensation range: $350,000—$850,000 USD
• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Pay

• Annual Salary: $350,000—$850,000 USD

Schedule

• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Qualifications

• Years of experience required will correlate with the internal job level requirements for the position.

Skills

• Expertise with accelerators (CUDA, ROCm, Triton, Pallas).
• ML framework programming (JAX or PyTorch).
• Work across the stack – kernels, model code, distributed systems.
• Balance research exploration with engineering implementation.
• Passionate about AI's potential and committed to developing safe and beneficial systems.
• Experience porting ML workloads between different types of accelerators.
• Familiarity with LLM training methodologies.

Benefits

• Annual compensation range: $350,000—$850,000 USD

Pay

• Annual Salary: $350,000—$850,000 USD

Schedule

• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Qualifications

• Years of experience required will correlate with the internal job level requirements for the position.

Skills

• Expertise with accelerators (CUDA, ROCm, Triton, Pallas).
• ML framework programming (JAX or PyTorch).
• Work across the stack – kernels, model code, distributed systems.
• Balance research exploration with engineering implementation.
• Passionate about AI's potential and committed to developing safe and beneficial systems.
• Experience porting ML workloads between different types of accelerators.
• Familiarity with LLM training methodologies.

Benefits

• Annual compensation range: $350,000—$850,000 USD

Pay

• Annual Salary: $350,000—$850,000 USD

Schedule

• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Qualifications

• Years of experience required will correlate with the internal job level requirements for the position.

Skills

• Expertise with accelerators (CUDA, ROCm, Triton, Pallas).
• ML framework programming (JAX or PyTorch).
• Work across the stack – kernels, model code, distributed systems.
• Balance research exploration with engineering implementation.
• Passionate about AI's potential and committed to developing safe and beneficial systems.
• Experience porting ML workloads between different types of accelerators.
• Familiarity with LLM training methodologies.

Benefits

• Annual compensation range: $350,000—$850,000 USD

Pay

• Annual Salary: $350,000—$850,000 USD

Schedule

• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Qualifications

• Years of experience required will correlate with the internal job level requirements for the position.

Skills

• Expertise with accelerators (CUDA, ROCm, Triton, Pallas).
• ML framework programming (JAX or PyTorch).
• Work across the stack – kernels, model code, distributed systems.
• Balance research exploration with engineering implementation.
• Passionate about AI's potential and committed to developing safe and beneficial systems.
• Experience porting ML workloads between different types of accelerators.
• Familiarity with LLM training methodologies.

Benefits

• Annual compensation range: $350,000—$850,000 USD

Pay

• Annual Salary: $350,000—$850,000 USD

Schedule

• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Qualifications

• Years of experience required will correlate with the internal job level requirements for the position.

Skills

• Expertise with accelerators (CUDA, ROCm, Triton, Pallas).
• ML framework programming (JAX or PyTorch).
• Work across the stack – kernels, model code, distributed systems.
• Balance research exploration with engineering implementation.
• Passionate about AI's potential and committed to developing safe and beneficial systems.
• Experience porting ML workloads between different types of accelerators.
• Familiarity with LLM training methodologies.

Benefits

• Annual compensation range: $350,000—$850,000 USD

Pay

• Annual Salary: $350,000—$850,000 USD

Schedule

• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Logistics