Senior Director, AI Model LifeCycle

What You’ll Be Working On

• Building a Team of Machine Learning Experts and being the Site leader for the Model Life Cycle Team.
• 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.
• RFT and Reinforcement learning to the fine tuning and training sections.
• Distillation and reinforcement learning pipelines (e.g., preference optimization, policy optimization, reward modeling).
• Dataset, model, and experiment management: versioning, lineage, evaluation, and reproducible fine-tuning at scale.

What You’ll Bring to the Team

• Advanced degree in Computer Science, Engineering, or a related field.
• 10+ years of industry experience leading and driving impactful projects in the AI Space.
• Lead and mentor a team of engineers with exceptional interpersonal skills, working autonomously while proactively collaborating with stakeholders at all levels.
• Experience in Generative AI (Large Language Models, Multimodal).
• Hands-on experience training, fine-tuning, and aligning LLMs using Reinforcement Learning and Reinforcement Fine-Tuning (RFT) techniques.
• Proactive and collaborative approach with the ability to work autonomously.
• Passion for building cutting-edge AI products and solving challenging technical problems.

Bonus Points:

• PhD in Machine Learning, Computer Science, NLP, or a related field strongly preferred.
• Research publications at NeurIPS, ICML, ICLR, ACL, EMNLP, or impactful preprints in the LLM post-training space.
• Proficiency in Golang or Python for large-scale, production-level services and PyTorch.
• Contributions to open-source AI projects such as vLLM or similar frameworks.
• Performance optimizations on GPU systems and inference frameworks.

Compensation Range

Compensation will be paid in the range of up to $301,750 - $355,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data.