Research Engineer, RL Engineering
Anthropic · San Francisco, CA | New York City, NY | Seattle, WA
Posted about 2 months ago
or apply directly on Anthropic's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 64 days Anthropic's roles stay open a median of 62 days
- Reposted
- No
- Salary listed
- No 0% of Anthropic's roles list one
- Ghost-job risk at Anthropic
- high 449 stale, 19 reposted of 603 open
- Hiring momentum
- 795 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-10-08
Measured from postings appearing on and disappearing from Anthropic's own greenhouse board since 2026-08-03. Full hiring picture for Anthropic.
About this role
As a Research Engineer in RL Engineering at Anthropic, you will build and improve the core reinforcement learning (RL) training system that supports both production and research efforts. Your role involves collaborating with various research teams to enhance the system's performance, implementing new training methods, and debugging complex issues. You will also communicate findings clearly and contribute to the understanding of RL training dynamics at scale.
- benefits
- 3/5
- freshness
- 1/5
- career value
- 5/5
- role clarity
- 5/5
- pay transparency
- 0/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Anthropic as an employer.
What you need
- Proficiency in Python and experience working in, debugging, and improving a large ML 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 ML framework (JAX, PyTorch, or similar)
- Ability to design controlled experiments and reach conclusions you and others can trust
- Ability to balance research exploration with engineering implementation
- Strong written and verbal communication skills
Nice to have
- Experience with reinforcement learning for large language models, in research, production, or both
- Experience studying training at scale: scaling behavior, training dynamics, or method development on large models
- Experience with large-scale distributed training systems
- Familiarity with LLM architectures and training methodologies
- Experience working close to a frontier training run
What you get
- Competitive compensation
- Optional equity donation matching
- Generous vacation and parental leave
- Flexible working hours
- Lovely office space for collaboration
Worth weighing
- No specific mention of remote work flexibility beyond the 25% office requirement
- Visa sponsorship is available but not guaranteed for all roles
- Salary range is quite broad, which may indicate variability based on experience or negotiation
Summarised from Anthropic's posting. Read the full original.
Listed by Anthropic on their greenhouse job board, last confirmed open on 2026-10-08. PitchMeAI is not the employer.
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