AI/ML Engineer - Hybrid Onsite In Eden Prairie, MN

Optum

Eden Prairie (MN)

On-site

USD 140,000 - 190,000

Full time

14 days+
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Benefits offered by this job

Comprehensive Benefits Package
Incentive Programs
Recognition Programs
Equity Stock Purchase
401k Contribution

Job summary

Optum is seeking a skilled ML engineer to develop and deploy machine learning solutions using LLMs and LangChain, with a focus on production-grade code and documentation.

The role requires 3+ years in ML with Python, Docker, and Git, and will involve fine-tuning and RAG-based optimization to deliver robust systems in a production environment, based in Eden Prairie, MN.

Qualifications

  • Requires 3+ years of experience with LLMs, machine learning, and professional Python coding.
  • Proficient in Docker, Git, and RAG techniques.
  • Authorized to work in the US without sponsorship.

Responsibilities

  • Develop and implement ML solutions using LLMs and LangChain.
  • Optimize models through fine-tuning and RAG methodologies.
  • Ensure production-quality code and documentation.

Skills

Large Language Models
Machine Learning
Python
LangChain
Retrieval-Augmented Generation
Docker
Git
XGBoost
K-means
PEP8
Containerization

Tools

Docker
Git
LangChain

Job description

Develop and implement machine learning solutions using LLMs and the LangChain framework. Optimize models through fine-tuning and RAG methodologies while ensuring production-quality code and documentation.

Requirements:
  • Requires 3+ years of experience with LLMs, machine learning, and professional Python coding. Candidates must be proficient in Docker, Git, and RAG techniques, and be authorized to work in the US without sponsorship.
Key Skills:
  • Large Language Models
  • Machine Learning
  • Python
  • LangChain
  • Retrieval-Augmented Generation
  • Docker
  • Fine-tuning
  • Git
  • XGBoost
  • K-means
  • PEP8
  • Containerization
Benefits:
  • Comprehensive Benefits Package
  • Incentive Programs
  • Recognition Programs
  • Equity Stock Purchase
  • 401k Contribution
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