Sr Model Engineer Rl Training Framework Jobs in San Francisco, CA

…that builds and owns the RL training system: the system that trains our production models and that researchers across Anthropic run their

As an RL post-training practitioner You have fine-tuned models for agentic tasks and made them measurably better.

training frameworks Solid background in reinforcement learning (RL) post-training infrastructure, RLHF, or automated model evaluation pipelines

Decisions in production training depend on knowing how the model is really behaving.

…sit at the heart of training intelligent, aligned, and general-purpose agents, including the systems that power various models.

Strong software engineering and infrastructure skills: data pipelines, training systems, evaluation frameworks, observability tooling, runtime monitors

The Principal Engineer is accountable for ensuring engineers can move efficiently from idea to trained model to deployed

As an engineer in RL Engineering, you'll work on keeping that system secure as it scales. This is a hands-on engineering role.

…in PyTorch or JAX for training large-scale models.

, evaluating and deploying ML models at scale Deep learning experience, especially with generative models, e.g., LLMs/VLMs, and/or reinforcement learning

As a Research Engineer on the Distributed Systems team within RL Engineering, you'll work on whatever part of that system is the current limit.

Design the data model for a kind of feedback we haven't collected before, and ship the pipeline that gets it into the training mix.

through reinforcement learning Pioneering fundamental RL research for large language models Building scalable RL infrastructure

…published or otherwise Experience developing RL algorithms for language models Experience with scaling laws or other quantitative models of training