# Senior Director, AI Model LifeCycle

**Company:** [Crusoe](https://hotfix.jobs/companies/crusoe)
**Location:** San Francisco, CA, Sunnyvale, CA
**Role:** ML Engineering
**Salary:** $302k – $355k/yr
**Experience:** 10+ years
**Skills:** PyTorch, Python, Go, LLMs, Reinforcement Learning, Fine-Tuning, Peft, Lora, Sft, Rft, vLLM, Gpu Optimization
**Posted:** 2026-04-24

> Leads AI Model LifeCycle team, building and managing fine-tuning, training pipelines for LLMs using techniques like PEFT, LoRA, RFT, and reinforcement learning. Requires 10+ years AI experience, advanced degree, hands-on LLM expertise, and team leadership skills.

## Job Description

## 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.

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