CrusoeCrusoe

Senior Software Engineer, AI Model Lifecycle

3mo ago
USASenior
CrusoeCrusoe

Senior Software Engineer, AI Model Lifecycle

3mo ago
USASeniormachine learningllm

Senior Software Engineer focused on building a managed platform for AI application development lifecycle including machine learning models and LLMs.

Nice to have

  • 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.

Conditions

  • 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 will be paid in the range of up to $172,425 - $230,945 + 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.
  • Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.

Other

  • Crusoe is on a mission to accelerate the abundance of energy and intelligence . As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.
  • We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.
  • We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.
  • If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.
  • The Senior Software Engineer for the AI Model Lifecycle team will play a crucial role in building a comprehensive managed platform for the entire application development lifecycle, with a specific focus on leveraging Machine Learning models, including Large Language Models (LLMs).
  • 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.
  • 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.