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CrusoeCrusoeSan Francisco, CA

Senior Software Engineer, AI Model LifeCycle

Builds and maintains platforms for fine-tuning, training, and managing LLMs including reinforcement learning pipelines and multi-node orchestration. Requires 4+ years in AI, hands-on LLM experience, and advanced degree in CS/Engineering.

172k – 231k/yr
On-site4+ YOEML Engineering

About the role

What You’ll Be Working On

  • 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.
  • 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.

Bonus Points:

  • 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

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 applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data.

Skills

PyTorchLLMsReinforcement LearningFine-TuningPeftLoraSftRftvLLMGoPythonGPUMulti-Node OrchestrationDataset Versioning

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