- San Francisco, California, United States
- Full-time · Senior
- $250K–$300K per year
- 4+ years
Build a comprehensive managed platform for the AI Model Lifecycle, focusing on fine‑tuning, training, and deployment of large language models.
Compensation
Compensation will be paid in the range of up to $250,000 - $300,000 + Bonus. Restricted Stock Units are included in all offers.
Responsibilities
- Manage fine‑tuning systems for large foundation models (SFT, PEFT, LoRA, adapters), including multi‑node orchestration, checkpointing, failure recovery, and cost‑efficient scaling.
- Implement and maintain end‑to‑end training pipelines for Large Language Models.
- Apply RFT and reinforcement learning to fine‑tuning and training.
- Develop distillation and reinforcement learning pipelines (e.g., preference optimization, policy optimization, reward modeling).
- Manage dataset, model, and experiment lifecycle: versioning, lineage, evaluation, and reproducible fine‑tuning at scale.
Requirements
- Advanced degree in Computer Science, Engineering, or a related field
- Nice to have: contributions to open‑source AI projects such as vLLM
- Nice to have: performance optimizations on GPU systems and inference frameworks