Member of Technical Staff, Post-Training

Job summary

Responsibilities

Advance the state of the art for model post training, ship state of the art models to production, and bridge the gap between research and production. We have one of the highest ratio of compute to engineers in the world. We do not delineate strongly between engineering and research.

• Design and write high-performant and scalable software for training models.
• Consistently post-train the models to reach SOTA level performance.
• Coordinate with other specialist teams (Agentic, Code…) to produce models that have strong all encompassing performance.
• Craft and implement techniques to improve the performance and results of our training cycles both on the SFT and the RL regime.
• Research, implement, and experiment with ideas on our supercompute and data infrastructure.

What they're looking for

• Extremely strong software engineering skills.
• Proficiency in Python and related ML frameworks such as JAX, Pytorch and XLA/MLIR.
• Experience with distributed training infrastructures (Kubernetes, Slurm) and associated frameworks (Ray).
• Experience using large-scale distributed training strategies.
• Hands on experience on training large model at scale.

Tech stack

• Python
• JAX
• PyTorch
• Kubernetes
• Ray