Research Engineer - Reinforcement Learning Engineering
$500k - $850k/yr+ Optional equity donation matching
Mid
Bachelor's
Seattle, WA, USA+2 moreMore locations: San Francisco, CA, USA | New York, NY, USA
HybridHybrid policy expects staff to work from an office at least 25% of the time.
AI & Machine LearningAI Research
H1B Sponsorship Available
About the job
Requirements
- Proficiency in Python and experience working in, debugging, and improving a large machine learning codebase.
- Experience with large-scale machine learning training (reinforcement learning, pretraining, or post-training) or the systems that support it.
- Experience with at least one modern machine learning framework such as JAX or PyTorch.
- Ability to design controlled experiments and reach trustworthy conclusions.
- Ability to balance research exploration with engineering implementation.
- Strong written and verbal communication skills.
- Care about the societal impacts of the work and be committed to developing safe and beneficial systems.
- A bachelor's degree or an equivalent combination of education, training, and/or experience.
- A field relevant to the role, demonstrated through coursework, training, or professional experience.
Responsibilities
- Build, own, and improve the core reinforcement learning training system that serves production and research runs.
- Work across orchestration, environments, training, inference, and evaluation wherever the system needs it.
- Study how reinforcement learning training behaves at scale and contribute to research that improves it, collaborating with teams across the company.
- Implement new training methods as stable, fast, well-tested code.
- Improve the speed and efficiency of reinforcement learning training and evaluation through profiling, optimization, and benchmarking.
- Make the system easier for researchers to build on through clean abstractions, clear application programming interfaces, and automated testing.
- Debug difficult problems across the stack, from quietly drifting runs to distributed systems failures that appear at scale.
- Communicate results clearly in writing and discussion.
Desired Qualifications
- Experience with reinforcement learning for large language models in research, production, or both.
- Experience studying training at scale, including scaling behavior, training dynamics, or method development on large models.
- Experience with large-scale distributed training systems.
- Familiarity with large language model architectures and training methodologies.
- Experience working close to a frontier training run.
- Experience profiling and optimizing the performance of machine learning workloads.
- Experience with reinforcement learning environments, evaluations, or sandboxed code execution.
- Experience with Rust or C++.
About the company
Anthropic builds the Claude family of AI models and sells them to businesses, software developers, and consumers, with research on making AI safe and understandable at the center of its work. In 2024 it introduced the Model Context Protocol, an open standard for connecting AI assistants to outside apps and data that OpenAI and Google adopted the next year. People use the Claude app to write and analyze files, programmers hand coding tasks to Claude Code, and companies build Claude into their own products through its API. Anthropic earns money from subscriptions, business plans, and usage-based API fees. Siblings Dario and Daniela Amodei founded Anthropic in 2021 with other former OpenAI employees, and it is based in San Francisco.
Company Size
5,001-10,000
Company Stage
Debt Financing
Total Funding
$243.8B
Headquarters
San Francisco, California
Founded
2021
Get referred to Anthropic
See people who can refer or advise you
Simplify's Take
What believers are saying
- Sales are multiplying: Anthropic's yearly revenue pace topped $65 billion in July 2026, over sevenfold since December 2025.
- IPO plans advanced: October 2026 reports describe investor meetings and a mid-November listing target; staff shares face lockups.
- Lower office minimum: 627 of 646 Anthropic job posts in October 2026 require at least 25% office time.
What critics are saying
- Job security rides on growth: Anthropic's IPO prospectus lists $518 billion in cloud and computing bills due in coming years.
- Defense work stays off-limits: in September 2026, appeals judges voted 2-1 to let the Pentagon keep blacklisting Anthropic.
- Growth is priced in: Anthropic's valuation reached $965 billion in May 2026, up from $380 billion in February.
What makes Anthropic unique
- Investors don't control its board alone: Anthropic's independent Long-Term Benefit Trust elects a growing number of directors.
- It isn't tied to one chipmaker: Claude runs on Nvidia GPUs plus custom AI chips designed by Google and Amazon.
- It holds back its riskiest model: Claude Mythos 5.1, launched September 2026, goes only to vetted cyberdefenders and life scientists.
Help us improve and share your feedback! Did you find this helpful?
Benefits
- Flexible Work Hours
- Paid Vacation
- Parental Leave
- Hybrid Work Options
- Company Equity