# Member of Technical Staff - ML Infrastructure Engineer, Post-training at Preference Model Labs

- Company: Preference Model Labs
- What the company does: Preference Model is building the next generation of training data to power the future of AI. Backed by a16z and South Park Commons.
- Company website: https://www.preferencemodel.com
- Type: Startups (AI role)
- Level: Senior
- Location: San Francisco
- Work setup: On-site
- Pay: $200K to $350K base salary per year (USD)
- Posted: 2026-09-11
- Apply by: 2026-10-26
- Apply: https://jobs.ashbyhq.com/Preference-Model/96e7f7d7-3fb5-48d8-ba18-a7ebce54a9be
- Page: https://www.1752.vc/careers/jobs/preference-model-labs-member-of-technical-staff-ml-infrastructure-engineer-post/

## About the role

Frontier research moves only as fast as its infrastructure permits. Building solid infrastructure is foundational to our mission of pushing self-directed learning as far as it can go.

## What they're looking for

- Strong software engineering fundamentals and hands-on experience building production-grade LLM inference and training infrastructure (ideally from the ground up)
- Experience building LLM training/inference internals such as transformers, distributed training, and working on inference libraries like vLLM, SGLang, Megatron
- Experience working on RL training frameworks like Slime, veRL, Ray Train, SkyRL
- Significant experience and understanding of distributed systems principles, and have hands-on experience with cloud platforms (AWS, GCP) and container orchestration (Kubernetes), building systems for high-throughput, low-latency workloads
- Have experience with data engineering tools and building robust, scalable data pipelines
- Proficiency in core ML frameworks such as PyTorch or JAX

Tags: Engineering