Member of Engineering – Reinforcement Learning Infrastructure
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Job Description
Working on the reinforcement learning team to improve reasoning and coding abilities of Large Language Models. Access to thousands of GPUs and hands-on role in applied research and infrastructure.
Responsibilities:
- Keep up with the latest research, and be familiar with the state of the art in LLMs, RL, and code generation
- Develop methods for tuning training and inference end-to-end for high throughput
- Design data control systems in an RL pipeline that govern what the model sees and when
- Debug cases where infrastructure decisions are silently degrading learning dynamics
- Build observability tooling that surfaces when a system-level issue is the root cause of a training regression
- Help build robust, flexible and scalable RL pipelines
- Optimize performance across the stack — networking, memory, compute scheduling, and I/O
- Write high-quality, pragmatic code
- Work in the team: plan future steps, discuss, and always stay in touch
Requirements:
- Experience with LLMs and model post-training workflows
- Understanding how Reinforcement Learning works and what its main bottlenecks are
- Solid software engineering fundamentals (testing, code review, debugging complex systems)
- Proficiency in Python with knowledge of concurrency, asynchronous programming, multiprocessing and performance optimization
- Familiarity with deep learning frameworks (PyTorch or JAX) and RL workflows (rollouts, replay buffers, policy updates)
- Experience designing and maintaining distributed RL training systems
- Experience with large-scale LLM training infrastructure
- Experience with profiling tools across the stack (e.g. py-spy)
- Experience with inference stacks (e.g. vLLM)
- Nice to have: Open-source contributions to RL or distributed ML projects
Benefits:
- Fully remote work & flexible hours
- 37 days/year of vacation & holidays
- Health insurance allowance for you and dependents
- Company-provided equipment
- Wellbeing, always-be-learning and home office allowances
- Frequent team get togethers
- Great diverse & inclusive people-first culture
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