Lead ML Engineer: Scalable AI for Legal Analytics

LexisNexis Risk Solutions; Raleigh (NC); On-site; USD 115,000 - 192,000; Full time

Benefits offered by this job

Annual incentive bonus

Country-specific benefits

Disability accommodation support

Job summary

LexisNexis Legal & Professional is seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures for next-generation legal research products. You will lead a team of 4–5 ML engineers, set platform direction, and ensure enterprise-grade scalability and responsible AI compliance.

The role combines deep ML expertise with distributed systems engineering, and requires hands-on leadership to guide product-wide ML initiatives across global

Qualifications

• 8–10 years of ML/Software Engineer experience.
• 2–3 years of people management experience.
• Master's degree or Bachelor's in computer science.
• Strong software engineering background for large-scale unstructured data.
• Experience deploying ML to production.

Responsibilities

• Lead, mentor, and grow a team of 4-5 ML engineers.
• Architect distributed ML systems serving multiple global products.
• Define engineering best practices for ML design, testing, and deployment.
• Establish CI/CD standards for ML lifecycle management.
• Ensure compliance with enterprise data governance and responsible AI standards.

Skills

Machine Learning

Software Engineering

People management

Leadership

Distributed systems

Education

Master's/Bachelor's in CS

Tools

Python

LLM serving

CI/CD

Retrieval systems

Cloud platforms

Job description

LexisNexis Legal & Professional is seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures for next-generation legal research products. You will lead a team of 4–5 ML engineers, set platform direction, and ensure enterprise-grade scalability and responsible AI compliance.

The role combines deep ML expertise with distributed systems engineering, and requires hands-on leadership to guide product-wide ML initiatives across global