Lead ML Engineer: Production AI/LLM & MLOps

RELX; East Devon; On-site; GBP 110,000 - 150,000; Full time

Benefits offered by this job

Generous holiday allowance

Private medical benefits

Pension scheme

Life assurance

Job summary

LexisNexis GTO is seeking a Machine Learning Engineering Lead to design, build, and deploy scalable ML systems for legal content products. You will guide architecture, MLOps, responsible AI, and AWS-based delivery while coordinating with cross-functional teams.

The role emphasizes hands-on engineering, system design, and governance with no direct reports, but mentoring of engineers as needed to advance critical AI/ML capabilities across platforms.

Qualifications

• Hands-on experience in ML engineering, software engineering, or data engineering.
• Experience deploying ML/AI systems in production.
• Experience integrating ML/AI with enterprise systems and APIs.
• Experience with AWS and cloud-hosted production environments.
• Equivalent technical experience or education considered.

Responsibilities

• Escalation point for AI/ML engineering issues within the area of responsibility.
• Design, build, deploy, and operate production AI/ML and LLM-based services for legal research and analytics.
• Implement RAG, semantic search, embeddings, and content enrichment where appropriate.
• Design agentic workflows and multi-step AI processes that are reliable and governable.
• Integrate AI/ML capabilities with enterprise systems and AWS-hosted services.
• Mentor and train engineers in AI/ML engineering, MLOps, and SDLC practices.
• Keep abreast of AI/ML developments and responsible AI practices.

Skills

Python development

ML engineering

AWS cloud

MLOps

LLM/RAG

Software architecture

mentoring

Education

Bachelor's degree in CS/EE

Tools

GitHub Copilot

Docker

Kubernetes

Terraform

REST APIs

Job description

LexisNexis GTO is seeking a Machine Learning Engineering Lead to design, build, and deploy scalable ML systems for legal content products. You will guide architecture, MLOps, responsible AI, and AWS-based delivery while coordinating with cross-functional teams.

The role emphasizes hands-on engineering, system design, and governance with no direct reports, but mentoring of engineers as needed to advance critical AI/ML capabilities across platforms.