Senior Software Engineer, AI Model Lifecycle
$172k - $231k • San Francisco, CA - US • FullTime
Posted 5mo ago
Remote Work Policy
On-site
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
Crusoe is seeking a Senior Software Engineer for their AI Model Lifecycle team to build a comprehensive managed platform for the entire application development lifecycle, with a specific focus on leveraging Machine Learning models, including Large Language Models (LLMs). This role is crucial in accelerating the abundance of energy and intelligence by powering ambitious AI workloads. The ideal candidate will be a problem-solving, opportunity-finding teammate with a sense of urgency, who believes in the scale of Crusoe's ambition and thrives on a path not fully paved.
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.
- Integrate RFT and Reinforcement learning into fine-tuning and training sections.
- Develop distillation and reinforcement learning pipelines (e.g., preference optimization, policy optimization, reward modeling).
- Manage dataset, model, and experiment versioning, lineage, evaluation, and reproducible fine-tuning at scale.
Requirements
- Advanced degree in Computer Science, Engineering, or a related field.
- 4-5+ years of industry experience leading and driving impactful projects in the AI Space.
- 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.
- Proficiency in Golang or Python for large-scale, production-level services and PyTorch.
- Experience with 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