Senior NLP/LLM Engineer — Legal AI in Production

Latitude; Ann Arbor (MI); Hybrid; USD 110,000 - 235,000; Full time

Benefits offered by this job

Hybrid work

Mental health days

Tuition reimbursement

Employee stock purchase plan

Job summary

Thomson Reuters is seeking a Senior Machine Learning Engineer to design, train, and deploy ML/LLM solutions that extract insights from complex legal documents. You will lead production systems for information extraction, text generation, summarization, and document analysis with a strong emphasis on robust evaluation and bias awareness.

The role blends hands-on model development with cross-functional collaboration across ML, engineering, product, legal, data, and security teams.

Qualifications

• Master’s degree in ML/CS/Statistics or related quantitative field.
• 3+ years of professional ML engineering, applied ML, or related software engineering experience.
• Hands-on experience building, training, and deploying ML models into production.

Responsibilities

• Design, build, train, and deploy ML/LLM models and systems for NLP and document intelligence.
• Develop production solutions for information extraction, text generation, summarization, AI agents, search, or document analysis.
• Build scalable ML pipelines for training, evaluation, deployment, and production use.

Skills

ML engineering

NLP

PyTorch

TensorFlow

Production deployment

Model evaluation

Information extraction

Python

LLM

Collaboration

Education

Master's degree in ML/CS/Statistics

Tools

PyTorch

TensorFlow

Job description

Thomson Reuters is seeking a Senior Machine Learning Engineer to design, train, and deploy ML/LLM solutions that extract insights from complex legal documents. You will lead production systems for information extraction, text generation, summarization, and document analysis with a strong emphasis on robust evaluation and bias awareness.

The role blends hands-on model development with cross-functional collaboration across ML, engineering, product, legal, data, and security teams.