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Preference Model is building automated ML research engineering to advance frontier AI models. The company is developing RL training environments that reflect real-world complexity, with diverse tasks and robust reward functions. The founding team has experience from Anthropic's data team, where they built data infrastructure and datasets behind Claude.
As a Senior ML Infrastructure Engineer, you will design, build, and scale the compute, scheduling, and data infrastructure powering post-training research on large language models. You'll develop and maintain core ML framework primitives and internal tooling that researchers depend on daily, accelerating reproducible experimentation and reducing iteration time. Your work will include building evaluation and benchmarking infrastructure, monitoring, logging, debugging tooling, automated testing, and deployment systems to catch failures early and maintain reliability at scale.
You'll partner directly with Research Engineers to translate research needs into infrastructure requirements and ship fast based on their feedback. This role requires strong software engineering fundamentals and production-grade infrastructure experience, ideally in ML or data-intensive systems. You should be proficient in PyTorch or JAX, with significant hands-on experience in distributed systems, cloud platforms (AWS, GCP), and container orchestration (Kubernetes). Experience building high-throughput, low-latency systems is essential.
You'll need expertise with data engineering tools and scalable data pipelines, plus experience with RL training frameworks like Slime, veRL, or Ray. Familiarity with LLM training/inference internals—transformers, distributed training, and inference libraries like vLLM or SGLang—is valuable. The ideal candidate balances production rigor with fast-moving research pace and communicates infrastructure tradeoffs clearly to non-specialist researchers.
The company offers competitive cash and equity compensation (>90th percentile), ownership and autonomy in a fast-moving startup, opportunity to work alongside senior and staff engineers from frontier labs and infrastructure companies, health/vision/dental benefits, 401K match, daily onsite lunch, weekly snacks, and visa sponsorship with relocation support.
