Member of Technical Staff, Post-Training
Core
Design and write high-performant, scalable software for training frontier AI models, specifically focusing on post-training phases to achieve state-of-the-art performance.
Role type
Senior IC machine-learning engineer (post-training)
Builds
Production-ready frontier AI models for content generation, semantic search, RAG, and agents
Domain
Artificial Intelligence / Large Language Models
Deliverable
production ML models
Required skills
Python, JAX, PyTorch, XLA/MLIR, distributed training infrastructures (Kubernetes, Slurm), Ray, large-scale distributed training strategies, post-training optimization
Preferred skills
Publications at top-tier venues (NeurIPS, ICML, ICLR, etc.)
Technologies
Kubernetes, Slurm, Ray, JAX, PyTorch, XLA, MLIR
Responsibilities
Design and write high-performant and scalable software for training models; Post-train models to reach SOTA level performance; Coordinate with specialist teams to produce models with strong all-encompassing performance; Craft and implement techniques to improve performance in SFT and RL regimes; Research, implement, and experiment with ideas on supercompute and data infrastructure
Seniority
Senior, hands-on IC
