# Research Engineer, RL Scaling Science

**Company:** [Anthropic](https://hotfix.jobs/companies/anthropic)
**Location:** London, United Kingdom
**Role:** ML Engineering
**Salary:** £375k – £640k/yr
**Skills:** Reinforcement Learning, Python, Machine Learning, Distributed Systems, Large-Scale Training, Long-Horizon Rl, Benchmarking, Experiment Design, Production Training, Debugging, Scaling Laws
**Posted:** 2026-08-03

> Conduct large-scale reinforcement learning experiments, develop long-horizon benchmarks, investigate scaling behavior, and translate validated research into production training recipes. The role requires strong empirical research skills, Python, distributed ML experience, and a bachelor's degree or equivalent experience.

## Job Description

## Responsibilities

- 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 between research and infrastructure, including failures that appear only at scale.
- Partner closely with adjacent reinforcement learning teams across research and engineering and advance the overall reinforcement learning stack.

## Requirements

- 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 and systems boundary, including debugging where the two meet.
- Care about the societal impacts of artificial intelligence and responsible scaling.
- Bachelor's degree or an equivalent combination of education, training, and experience in a relevant field, as demonstrated through coursework, training, or professional experience.

## Nice-to-haves

- 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 through reinforcement learning interventions.
- Experience working on frontier-scale training runs with long trajectories.

## Representative Projects

- 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.

## Compensation and Benefits

- Annual salary: **£375,000–£640,000 GBP**.
- Hybrid policy: staff are expected to work from an office at least 25% of the time; some roles may require more office time.
- Visa sponsorship is available for eligible roles and candidates.
- Competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office collaboration space.

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