ML Engineer Lead | Build Scalable, Responsible AI Platform

Remitly; Raleigh (NC); On-site; USD 115,000 - 192,000; Full time

Benefits offered by this job

Annual incentive bonus

Job summary

LexisNexis Legal & Professional in the United States seeks a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products.

You will lead a hands-on team of 4-5 ML engineers, drive platform-level decisions, and ensure enterprise-grade scalability, reliability, and responsible AI compliance across global products.

Qualifications

• 8-10 years of Machine Learning/Software Engineer experience.
• 2-3 years of people management experience.
• Master’s degree or bachelor’s degree, computer science degree is highly desirable.
• Strong software engineering background with experience in building system design, architecting AI features/products for large user bases and unstructured data.
• Experience with ML deployment to production.

Responsibilities

• Lead, mentor, and grow a team of 4-5 ML engineers.
• Provide architectural direction and code-level guidance.
• Establish engineering best practices for ML system design, testing, and deployment.
• Architect distributed ML systems serving multiple global products.
• Define and implement enterprise-ready agentic frameworks and deterministic vs. autonomous workflows.
• Lead decisions on guardrails, safety layers, and traceability mechanisms.

Skills

ML/Software engineering experience

People management

CS degree

Systems design

ML deployment to production

Education

Bachelor’s or Master’s in CS

Job description

LexisNexis Legal & Professional in the United States seeks a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products.

You will lead a hands-on team of 4-5 ML engineers, drive platform-level decisions, and ensure enterprise-grade scalability, reliability, and responsible AI compliance across global products.