- Somerville, Massachusetts, United States
- Hybrid
Applied Scientists own the mastery of new frontier model capabilities, including developing post-training recipes for learning a wide range of dexterous tasks. This role is a hybrid of research, engineering, and operations.
Responsibilities
- Owning end-to-end improvement of target capabilities, from baseline performance to mastery
- Designing task suites and evaluation protocols that faithfully capture what research, science partners, and customers need, and that generalize beyond any single deployment
- Coordinating data collection, training and fine-tuning models, sweeping data mixtures and configurations, and orchestrating large-scale evaluations
- Running rigorous experimental analysis across model variants — isolating variables, quantifying statistical confidence, and diagnosing failure modes from rollout data
- Using the stack in new ways rather than redesigning it — and when a capability is fundamentally restricted, you'll work with the pretraining and post-training teams to improve the model
Requirements
- PhD in a relevant area