11 hours ago
Base Salary
$250k - $300k/yr
Responsibilities
- Manage fine-tuning systems for large foundation models using SFT, PEFT, LoRA, and adapters, including multi-node orchestration, checkpointing, failure recovery, and cost-efficient scaling.
- Implement and maintain end-to-end LLM training pipelines.
- Build reinforcement fine-tuning and reinforcement learning pipelines, including preference optimization, policy optimization, and reward modeling.
- Develop distillation pipelines.
- Manage dataset, model, and experiment versioning, lineage, evaluation, and reproducible fine-tuning at scale.
- Lead and drive impactful AI projects and build production-level AI services.
Requirements
- Advanced degree in Computer Science, Engineering, or a related field.
- 4–5+ years of industry experience leading and driving impactful projects in AI.
- Experience with Generative AI, including large language models and multimodal systems.
- Hands-on experience training, fine-tuning, and aligning LLMs using reinforcement learning and reinforcement fine-tuning techniques.
- Proficiency in Golang or Python for large-scale, production-level services is preferred.
- Experience with PyTorch is preferred.
- Contributions to open-source AI projects such as vLLM or similar frameworks are preferred.
- Experience optimizing performance on GPU systems and inference frameworks is preferred.
- Ability to work proactively, collaboratively, and autonomously.
Benefits
- Competitive compensation, bonus eligibility, and restricted stock units.
- Paid time off and paid holidays.
- Comprehensive health, dental, and vision insurance.
- Employer HSA contributions.
- Paid parental leave.
- Paid life insurance and short- and long-term disability coverage.
- Professional development and tuition reimbursement.
- Mental health and wellness support.
- Commuter benefits for parking and transit.
- Cell phone stipend.
- 401(k) retirement plan with company match up to 4% of salary.
- Volunteer time off.
Categories
About Crusoe
Crusoe builds and operates GPU-powered data centers and an AI cloud platform for enterprises running large-scale AI training and inference. It vertically integrates energy supply with compute, using stranded and renewable power to reduce emissions and costs, and sells capacity via cloud services and managed infrastructure. Founded in 2018 and headquartered in Denver, the company is privately held.