Research Engineer - RL Scaling Science
About the job
- Strong empirical research skills in reinforcement learning, large-scale machine learning training, or a closely adjacent area.
- Demonstrated ability to own large experiments end-to-end, from design through interpretation.
- Proficiency in Python and experience working with large-scale or distributed machine learning systems.
- Comfort operating at the research/systems boundary, including debugging where the two meet.
- Care about the societal impacts of artificial intelligence and responsible scaling.
- A bachelor's degree or an equivalent combination of education, training, and/or experience; relevant field of study demonstrated through coursework, training, or professional experience.
- Design, run, and interpret large-scale reinforcement learning experiments, reasoning rigorously about what the data does and does not show.
- Investigate how reinforcement learning improves as horizon, compute, and model size grow.
- Build and maintain benchmarks for long-horizon reinforcement learning so progress is measurable and reproducible.
- Translate validated findings into production training recipes, exercising judgment about when a result is robust enough to ship.
- Debug complex issues at the seam where research meets infrastructure, including failures that only appear at scale.
- Partner closely with adjacent reinforcement learning teams across research and engineering and advance the overall reinforcement learning stack.
- Design a benchmark suite for long-horizon reinforcement learning that distinguishes genuine capability gains from artifacts of evaluation setup.
- Take a promising experimental finding, stress-test it across model scales, and work with training teams to land it in a production recipe.
- Investigate an unexpected scaling trend in a reinforcement learning run and trace it to a root cause spanning algorithm, data, and infrastructure.
- Published or shipped work in long-horizon reinforcement learning or reinforcement learning fundamentals.
- Experience translating research findings into production training recipes.
- Demonstrated large-scale industry impact via reinforcement learning interventions.
- Experience working on frontier-scale training runs with long trajectories.
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
N/A
Total Funding
$243.8B
Headquarters
San Francisco, California
Founded
2021
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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.
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Benefits
- Flexible Work Hours
- Paid Vacation
- Parental Leave
- Hybrid Work Options
- Company Equity