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 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. You will partner with research engineers to translate needs into infrastructure requirements and ensure reproducible, high-throughput experimentation.

• Design, build, and scale compute, scheduling, and data infrastructure for post-training RL
• Develop and maintain core ML framework primitives and internal tooling
• Build evaluation, benchmarking, monitoring, logging, and automated testing systems
• Partner with Research Engineers to translate research needs into infrastructure requirements
• Strong software engineering fundamentals and experience with LLM training/inference infrastructure
• Experience with distributed systems, cloud platforms (AWS/GCP), and Kubernetes