Lead ML Engineer: Production AI & LLM Systems

RELX International; Farringdon; On-site; AUD 180,000 - 240,000; Full time

Job summary

RELX International is seeking a Machine Learning Engineering Lead to drive production ML and AI initiatives across legal content platforms. You will shape architecture, implement agentic workflows, and guide teams in responsible AI and MLOps practices.

The role emphasizes scalability, reliability, and cross-functional collaboration in a cloud-first environment. Lead the design and delivery of advanced ML services, work with LLM/RAG capabilities, and ensure robust governance, testing, and

Qualifications

• Significant hands-on experience in machine learning engineering, software engineering, or a related technical discipline.
• Experience designing, building, deploying, and operating ML, AI, LLM, or data-driven systems in production.
• Experience integrating AI/ML services with enterprise systems, APIs, databases, data platforms, legacy applications, or internal services.
• Experience working with AWS or cloud-hosted production environments.
• Strong Python development skills for ML engineering, data processing, and production workflows.
• Understanding of ML engineering, MLOps, CI/CD, testing, monitoring, and observability.

Responsibilities

• Design, build, deploy, and operate production AI/ML and LLM-based services for legal content products.
• Provide technical direction on architecture, MLOps, responsible AI, and integration with enterprise systems.
• Mentor engineers and promote best practices in SDLC, code reviews, and AI-assisted development tools.
• Collaborate with cross-functional teams to finalise requirements and ensure scalable, reliable AI solutions.

Job description

RELX International is seeking a Machine Learning Engineering Lead to drive production ML and AI initiatives across legal content platforms. You will shape architecture, implement agentic workflows, and guide teams in responsible AI and MLOps practices.

The role emphasizes scalability, reliability, and cross-functional collaboration in a cloud-first environment. Lead the design and delivery of advanced ML services, work with LLM/RAG capabilities, and ensure robust governance, testing, and