The roleAs a research systems engineer, you'll train frontier-scale models and develop the methods that make continual learning work inside enterprise environments. You'll design and run experiments at scale, explore cutting-edge RL techniques, and build the tools that let us understand what's actually happening during training. This role sits at the intersection of research and systems. You'll invent new algorithms alongside researchers, then work with infrastructure engineers to run them on GPUs.
What you'll do- Post-train frontier-scale language models on enterprise tasks and environments
- Explore and develop RL techniques, co-designing algorithms and systems
- Contribute to Alchemy, our data research program for generating signal-rich training environments from production data
- Build high-performance internal tools for probing, debugging, and analyzing training runs
- Partner with infrastructure engineers to scale training and inference efficiently
What we're looking for- Experience training or serving large language models
- Experience building RL environments and evaluations for language models
- Proficiency in PyTorch, JAX, or similar ML frameworks, with experience in distributed training
- Strong experimental design skills - you know how to set up experiments that actually answer questions
Strong candidates also have- Background in pre-training or post-training research
- Previous experience in high-performance computing environments or large-scale clusters
- Contributions to open-source ML research or infrastructure
- Demonstrated technical creativity through published research, OSS contributions, or side projects
Benefits & LogisticsThis role is based in San Francisco. We work from our office in the Mission. We offer:
- Competitive compensation and equity
- Generous health benefits
- Unlimited PTO
- Paid parental leave
- Daily lunches and dinners
- Transportation and relocation support
- Retirement plans
We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the process with you. We encourage you to apply even if you do not believe you meet every single qualification.
