Member of Technical Staff, Integration/RL Team (Research Engineer)

Job summary

Responsibilities

The integration team is responsible for developing and scaling machine learning algorithms and infrastructure for LLM post-training, with a focus on large-scale, distributed RL methods. We strive for excellence in both engineering and science by meticulously designing experiments and design docs.

• Design and write high-performing and scalable software for training models.
• Develop new tools to support and accelerate research and LLM training.
• Coordinate with other engineering teams (Infrastructure, Efficiency, Serving) and the scientific teams (Agent, Multimodal, Multilingual, etc.) to create a strong and integrated…
• Craft and implement techniques to improve performance and speed up our training cycles, both on SFT, offline preference, and the RL regime.
• Research, implement, and experiment with ideas on our cluster and data infrastructure.

What they're looking for

• Extremely strong software engineering skills.
• Value test-driven development methods, clean code, and strive to reduce technical debts at all levels.
• Proficiency in Python and related ML frameworks such as JAX, Pytorch and/or XLA/MLIR.
• Experience using and debugging large-scale distributed training strategies (memory/speed profiling).
• [Bonus] Experience with distributed training infrastructures (Kubernetes) and associated frameworks (Ray).

Tech stack

• Python
• JAX
• PyTorch
• Kubernetes
• Ray