Senior Machine Learning Engineer

Salary: £45,000 - 85,000 per year

Requirements:

• Experience working with modern Python codebases.
• Experience with AWS or a comparable cloud platform, including infrastructure-as-code practices.
• Solid understanding of software engineering principles, techniques and delivery processes.
• Experience with generative AI and agentic AI systems.
• Strong interpersonal, communication and presentation skills, with the ability to engage varied audiences.
• Experience with Azure Pipelines and Terraform is desirable but not essential.

Responsibilities:

• Research and evaluate emerging AI technologies for customer-facing features.
• Design and build agentic AI systems and AI-powered product capabilities.
• Develop reusable frameworks for evaluating AI quality, safety and performance.
• Build scalable, high-performance and cost-efficient services.
• Work with Python, AWS services including EKS, S3 and RDS, Terraform, and AI, machine-learning and data-science libraries such as Google ADK, pandas and FAISS.
• Develop and evolve AWS platform infrastructure using Terraform, including RDS instances and EKS clusters.
• Mentor junior developers in engineering best practices, including test-driven development with pytest and idiomatic Python.
• Write and review detailed technical specifications for moderately complex system components.
• Participate in development processes, code reviews and Scrum ceremonies.
• Collaborate with stakeholders across the organisation.

Technologies:

• Agentic AI
• AI
• AWS
• Azure
• Cloud
• Data-Science
• Support
• Python
• Terraform
• pandas
• pytest

More:

We are LexisNexis Intellectual Property Solutions, helping the innovation community make better-informed decisions through products that support productivity, regulatory compliance and stronger outcomes. Our AI Platform team builds capabilities for our flagship analytics products, using modern, cloud-native infrastructure to develop practical AI features, tools and services. Our IP analytics platform combines curated, enriched datasets, analytical tools, workflows and visualisations for competitive intelligence, benchmarking and portfolio optimisation. This full-time role is based in Farringdon and offers flexible working hours. We support work-life balance through wellbeing initiatives, shared parental leave, study assistance and sabbaticals, with additional country-specific benefits. We are committed to an accessible hiring process and equal opportunity employment.

last updated 40 week of 2026