Machine Learning Engineer Lead

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

Benefits offered by this job

Annual incentive bonus

Country-specific benefits

Job summary

LexisNexis Legal & Professional, part of RELX, seeks a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that power next‑generation legal research and analytics products. You will be a hands‑on engineer and leader, guiding a team of 4–5 ML engineers and setting platform‑level decisions for enterprise‑grade scalability and responsible AI.

Required: 8–10 years of ML/Software Eng experience, 2–3 years in people management, a CS degree

Qualifications

• 8-10 years of Machine Learning/Software Engineer experience.
• 2-3 years of people management experience.
• Master's or Bachelor's degree in CS is highly desirable.
• Strong software engineering background with system design for large-scale, 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.
• Conduct design reviews, performance reviews, and technical roadmap planning.
• Architect distributed ML systems serving multiple global products.
• Standardize infrastructure patterns for LLM serving and retrieval systems.
• Define and implement enterprise-ready agentic frameworks.
• Architect multi-step reasoning systems.
• Lead decisions on deterministic workflows vs. autonomous agents.
• Implement guardrails, safety layers, and traceability mechanisms.
• Develop evaluation frameworks to measure reasoning quality, hallucination rates, and reliability.
• Establish CI/CD standards for ML lifecycle management.
• Ensure compliance with enterprise data governance and responsible AI standards.

Skills

Machine Learning

Software Engineering

Distributed Systems

Team Leadership

ML Deployment

Education

CS degree

Job description

About Our Team

LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX (www.relx.com), a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today’s top model creators for each individual legal use case. The company employs over 2,000 technologists, data scientists, and experts to develop, test, and validate solutions in line with RELX Responsible AI Principles (https://stories.relx.com/responsible-ai-principles/index.html).

About Our Team

LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX (www.relx.com), a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today’s top model creators for each individual legal use case. The company employs over 2,000 technologists, data scientists, and experts to develop, test, and validate solutions in line with RELX Responsible AI Principles (https://stories.relx.com/responsible-ai-principles/index.html).

About The Role

Do you love collaborating with teams to solve complex technical problems?

We are seeking 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. This role combines deep ML expertise with distributed systems engineering and AI platform development.

In this role you will be a hands-on engineer and leader that will lead a high-performing team of 4-5 ML engineers, drive platform-level decisions, and ensure enterprise-grade scalability, reliability, and responsible AI compliance.

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.
• Conduct design reviews, performance reviews, and technical roadmap planning.
• Architect distributed ML systems serving multiple global products.
• Standardize infrastructure patterns for LLM serving and retrieval systems.
• Define and implement enterprise-ready agentic frameworks.
• Architect multi-step reasoning systems.
• Lead decisions on deterministic workflows vs. autonomous agents.
• Implement guardrails, safety layers, and traceability mechanisms.
• Develop evaluation frameworks to measure reasoning quality, hallucination rates, and reliability.
• Establish CI/CD standards for ML lifecycle management.
• Ensure compliance with enterprise data governance and responsible AI standards.

Requirements

• 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 feature/products that caters large number of users and deals with large volume of unstructured data
• Experience with ML deployment to production

U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates. This job is eligible for an annual incentive bonus.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits.