Work at the intersection of research and engineering — implementing and scaling new ideas.
What you'll do
- Prototype, fine-tune, and ship models — including fine-tuning open-weight foundation models for our use cases
- Design evaluation harnesses and weigh build-vs-buy tradeoffs between self-hosted and frontier API models across accuracy, cost, and latency
- Help build the data flywheel — labeling pipelines, human-in-the-loop feedback, and drift monitoring
- Translate research literature into practice, and know when a published technique will or won't transfer to our data
What we're looking for
- 5+ years of experience in AI/ML research or applied research engineering
- Direct experience fine-tuning LLMs (e.g. supervised fine-tuning, LoRA/QLoRA, preference optimization)
- Strong data reasoning fundamentals — evaluation design, calibration, distribution shift
Languages
- Python
- C++
- Rust
Frameworks & tools
- PyTorch
- JAX
- Ray
- CUDA
- Kubernetes