About This Role:The Senior Director for the Model LifeCycle team will undertake a pivotal role in establishing both a dedicated team and a comprehensive managed platform to oversee the entire application development lifecycle, with a particular emphasis on utilizing Machine Learning models, including Large Language Models (LLMs).
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.
Benefits:- Competitive compensation
- Restricted Stock Units
- Paid time off & paid holidays
- Comprehensive health, dental & vision insurance
- Employer contributions to HSA account
- Paid parental leave
- Paid life insurance, short-term and long-term disability
- Professional development & tuition reimbursement
- Mental health & wellness support
- Commuter benefits (parking & transit)
- Cell phone stipend
- 401(k) Retirement plan with company match up to 4% of salary
- Volunteer time off
Compensation RangeCompensation 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 applicants knowledge, education, and abilities, as well as internal equity and alignment with market data.
