Member of Technical Staff - ML Platform Engineer
About The Position
Preference Model is hiring a Member of Technical Staff for its ML Platform team. The role owns the systems that take reinforcement-learning environments from a builder’s repository to a partner lab’s training run. This includes Karotte, the company’s open-source framework for defining RL environments; an internal platform for building, running, and reviewing environments on CPU, GPU, and TPU; and integrations for delivering environments to partner labs. The engineer will work closely with environment builders and post-training researchers on a small Platform team. A key goal for the first six months is to create a mostly automated delivery path to each partner lab, so environments marked ready are built, checked against lab requirements, and packaged without manual work. The role also includes adapting to other platform and infrastructure priorities as they change.
Requirements
- Strong software engineering fundamentals and a track record of building and operating production infrastructure or developer platforms used by other engineers.
- Proficiency in Python, including experience writing libraries and APIs for other users.
- Hands-on experience with containers and orchestration such as Docker, Kubernetes, or similar.
- Hands-on experience with at least one major cloud platform, such as GCP or AWS.
- Working understanding of safely running untrusted code, including isolation, resource limits, and handling processes that fill disk space or refuse to exit.
- Extensive hands-on use of coding agents such as Claude Code, Cursor, Codex, or similar, and an intuition for where models cut corners.
- Experience owning a tedious process end to end, such as a migration, release process, or delivery pipeline, and automating as much of it as possible.
Nice To Haves
- Experience building RL environments, evaluation harnesses, or agent benchmarks such as Terminal-Bench or SWE-bench.
- Familiarity with RL post-training and inference stacks such as verl, Ray, SkyPilot, vLLM, or SGLang.
- Experience building sandbox or code-execution infrastructure, including microVMs such as Firecracker or gVisor, at an infrastructure startup or frontier lab.
- Experience as an early platform or infrastructure engineer at a startup, building the internal platform used by the rest of engineering.
- Experience as a forward deployed or integrations engineer, deploying a company’s software in customers’ own environments.
- Experience building developer tooling or internal platforms used by ML researchers.
- Experience maintaining an open-source developer framework with external users.
Responsibilities
- Own integrations for delivering environments to partner labs, including building container images, matching lab submission formats, and automating pre-delivery requirements checks.
- Perform delivery work manually when necessary and automate it over time.
- Build and maintain Karotte, the open-source environment framework, including API design, releases, and migrations that preserve compatibility with existing environments.
- Run and scale infrastructure for building, running, and grading environments across CPU, GPU, and TPU.
- Implement containerized rollouts, VM-based sandboxing, resource limits, and isolation to prevent models from gaming their graders.
- Build internal tools used by environment builders, including a CLI, documentation, data catalog, access controls, and run monitoring.
- Work with environment builders and post-training researchers to turn recurring pain points into platform features.
- Ship platform improvements quickly in response to user feedback.
Benefits
- Competitive cash and equity compensation (>90th percentile).
- Ownership and autonomy in a fast-moving startup environment.
- Opportunity to work alongside senior and staff engineers from frontier labs and infrastructure companies, plus top ML engineers.
- Health, vision, and dental benefits.
- 401(k) match.
- Lunch provided every day onsite.
- Weekly snack orders.
- Visa sponsorship and relocation support available.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
