Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will develop alignment algorithms and loss functions to improve data efficiency, build data pipelines that prepare web data for model training, identify quality signals for real-world model performance, and design sampling algorithms that improve large generative model serving efficiency. You will write production-facing and training code and work with GPU-based systems and data infrastructure.
Requirements
- PhD or equivalent experience
- Ability to write clear production-facing and training code
- Experience working with GPUs for training, serving, and debugging
- Experience with data pipelines and data infrastructure
- Strong understanding of reinforcement learning and transformers
- Track record of exceptional research or creative applied ML projects
Responsibilities
- Develop alignment algorithms and loss functions to improve data sample efficiency
- Write data pipelines that process web data for model ingestion
- Identify quality signals for real-world model performance
- Design sampling algorithms to improve serving efficiency of large generative models
Benefits
- Equity
- Health coverage for employees and their families with most premiums covered
- 401(k) contribution
- Paid parental leave of up to 20 weeks
- Four weeks of PTO
- Daily in-office catering
- Monthly DoorDash stipend
- Monthly wellness stipend