# Senior Software Engineer, AI Model LifeCycle

**Company:** [Crusoe](https://hotfix.jobs/companies/crusoe)
**Location:** San Francisco, CA, Sunnyvale, CA
**Role:** ML Engineering
**Salary:** $172k – $231k/yr
**Experience:** 4+ years
**Skills:** PyTorch, LLMs, Reinforcement Learning, Fine-Tuning, Peft, Lora, Sft, Rft, vLLM, Go, Python, GPU, Multi-Node Orchestration, Dataset Versioning
**Posted:** 2026-03-20

> 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.

## Job Description

## 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.

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