Machine Learning Systems Engineer, RL Engineering
Develops and optimizes reinforcement learning systems and infrastructure for training large AI models like Claude, focusing on performance, reliability, and researcher productivity. Requires 4+ years software engineering experience.
About the job
You may be a good fit if you:
- Have 4+ years of software engineering experience
- Like working on systems and tools that make other people more productive
- Are results-oriented, with a bias towards flexibility and impact
- Pick up slack, even if it goes outside your job description
- Enjoy pair programming (we love to pair!)
- Want to learn more about machine learning research
- Care about the societal impacts of your work
Strong candidates may also have experience with:
- High performance, large scale distributed systems
- Large scale LLM training
- Python
- Implementing LLM finetuning algorithms, such as RLHF
Representative projects:
- Profiling our reinforcement learning pipeline to find opportunities for improvement
- Building a system that regularly launches training jobs in a test environment so that we can quickly detect problems in the training pipeline
- Making changes to our finetuning systems so they work on new model architectures
- Building instrumentation to detect and eliminate Python GIL contention in our training code
- Diagnosing why training runs have started slowing down after some number of steps, and fixing it
- Implementing a stable, fast version of a new training algorithm proposed by a researcher
Skills
Python, RLHF, Distributed Systems, Llm Training, Finetuning, Reinforcement Learning, Machine Learning Systems
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