Research Engineer, Performance RL (Reinforcement Learning)

Menlo Ventures; San Francisco (CA); Hybrid; USD 350,000 - 850,000; Full time

Benefits offered by this job

Competitive compensation

Generous vacation and parental leave

Flexible working hours

Job summary

Menlo Ventures is looking for a Research Engineer for their Code RL team. This role focuses on advancing AI models' coding capabilities while ensuring safety and performance in output.

The successful candidate should have expertise in machine learning frameworks and a Bachelor's degree or equivalent experience. The position offers competitive compensation, including a salary range of $350,000 to $850,000, and benefits including flexible working hours and a lovely office in San Francisco.

Qualifications

• Expertise with CUDA, ROCm, or other accelerators.
• Experience with ML frameworks like JAX or PyTorch.
• Ability to balance research and engineering.

Responsibilities

• Invent and implement RL environments and evaluations.
• Conduct experiments and shape the research roadmap.
• Deliver work into training runs.
• Collaborate with researchers and engineers across teams.

Skills

Expertise with accelerators (CUDA, ROCm, Triton, Pallas)

ML framework programming (JAX or PyTorch)

Experience with reinforcement learning

Knowledge of distributed systems

Education

Bachelor's degree in a related field

Job description

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the RL Teams

Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We contribute to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Sonnet 4.6 and Opus 4.6. Our work spans several key areas:

• Developing systems that enable models to use computers effectively
• Advancing code generation through reinforcement learning
• Pioneering fundamental RL research for large language models
• Building scalable RL infrastructure and training methodologies
• Enhancing model reasoning capabilities

We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implementing our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting‑edge research and engineering excellence, with a deep commitment to building high‑quality, scalable systems that push the boundaries of what AI can accomplish.

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.

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

You may be a good fit if you:

• Have expertise with accelerators (CUDA, ROCm, Triton, Pallas), ML framework programming (JAX or PyTorch).
• Have worked across the stack – kernels, model code, distributed systems.
• Know how to balance research exploration with engineering implementation.
• Are 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.

Compensation

Annual Salary: $350,000 - $850,000 USD

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.

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

Visa sponsorship: We sponsor visas where possible and will make reasonable efforts to obtain a visa if you receive an offer.

Benefits: We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in San Francisco.

How we’re different

We believe that the highest-impact AI research will be big science. Our team works as a single cohesive unit on large-scale research efforts and values impact over smaller puzzles. We prioritize communication skills and collaboration.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits. Learn about our policy for using AI in our application process.