Senior Staff AI Model Lifecycle Engineer

CRUSOE; Sunnyvale (CA); On-site; USD 250,000 - 300,000; Full time

Benefits offered by this job

Competitive compensation

Restricted Stock Units

Paid time off & holidays

Health, dental & vision insurance

HSA contributions

Paid parental leave

Life insurance & disability

Tuition reimbursement

Mental health support

Commuter benefits

Cell phone stipend

401(k) match up to 4%

Volunteer time off

Job summary

Crusoe is seeking a Senior Staff Software Engineer to lead the AI Model Lifecycle initiatives, building a comprehensive managed platform for the full application development lifecycle focused on LLMs and related AI workloads.

You will manage fine-tuning systems, training pipelines, and experimentation at scale, shaping cutting-edge AI products with a strong emphasis on reliability, performance, and cost efficiency.

Qualifications

• Advanced degree in Computer Science, Engineering, or a related field.
• 4-5+ years of industry experience leading AI projects.
• Experience in Generative AI and Large Language Models.
• Hands-on experience with Reinforcement Learning and Reinforcement Fine-Tuning (RFT).
• Ability to work autonomously and collaboratively.

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 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.

Skills

LLM training

Reinforcement Learning

Python/Golang

PyTorch

Foundation models

Education

Advanced degree in Computer Science or related field

Job description

Crusoe is seeking a Senior Staff Software Engineer to lead the AI Model Lifecycle initiatives, building a comprehensive managed platform for the full application development lifecycle focused on LLMs and related AI workloads.

You will manage fine-tuning systems, training pipelines, and experimentation at scale, shaping cutting-edge AI products with a strong emphasis on reliability, performance, and cost efficiency.