Member of Technical Staff - ML Infrastructure Engineer, Post-training

Preference Model is seeking a Senior ML Infrastructure Engineer to build and scale the systems powering frontier post-training research on large language models. This role involves designing compute, scheduling, and data infrastructure, developing core ML framework primitives, and creating evaluation and benchmarking tools to accelerate research and ensure reliability.

• Design, build, and scale compute, scheduling, and data infrastructure for post-training research
• Develop and maintain core ML framework primitives and internal tooling
• Build evaluation, benchmarking, monitoring, logging, and debugging tooling
• Partner with Research Engineers to translate needs into infrastructure requirements
• Experience with production-grade ML or data-intensive infrastructure
• Proficiency in PyTorch or JAX and distributed systems principles