Senior Machine Learning Engineer

Burns Sheehan; Greater London; On-site; GBP 110,000 - 150,000; Full time

Job summary

Burns Sheehan Limited is seeking a Senior AI/ML Engineer to build and scale production-grade AI systems within a WealthTech platform. You will work across LLMs, RAG, AI agents and traditional ML, delivering robust backend services and APIs.

The role emphasizes ownership from concept to production, with exposure to cloud infrastructure and MLOps pipelines in a regulated fintech environment. Strong Python skills and production experience are essential.

Qualifications

• Strong Python and software engineering fundamentals.
• Experience building and deploying AI/ML solutions into production.
• Hands-on experience with LLMs, RAG and AI agents.
• Experience developing backend services and APIs.
• Understanding of cloud infrastructure, Docker and Terraform.
• Experience with MLOps, model deployment and monitoring.
• Ability to take ownership of projects from initial concept through to production.

Skills

Python

Production ML

LLMs

AI agents

APIs

MLOps

Tools

Docker

Terraform

Vertex AI

GCP

Job description

I'm working with a fast-growing WealthTech business looking for a Senior AI/ML Engineer to help build and scale AI-powered solutions within their core technology platform.

The business has developed its own technology platform, helping financial advisers simplify complex processes, automate administrative work and deliver better outcomes for their clients.

They're now investing heavily in AI, with an exciting opportunity to build production-grade AI systems that solve real-world problems, from automating document processing to developing intelligent solutions that support complex financial decision-making.

This is a hands-on engineering role, working across LLMs, RAG, AI agents and traditional Machine Learning, with a real focus on building robust, scalable systems rather than just developing prototypes.

What they're looking for:

• Strong Python and software engineering fundamentals
• Experience building and deploying AI/ML solutions into production
• Hands-on experience with LLMs, RAG and AI agents
• Experience developing backend services and APIs
• Understanding of cloud infrastructure, Docker and Terraform
• Experience with MLOps, model deployment and monitoring
• Ability to take ownership of projects from initial concept through to production

Experience with GCP/Vertex AI, FinTech or regulated environments would be beneficial, but isn't essential.

This is a fantastic opportunity for an AI/ML Engineer with strong software engineering fundamentals who wants to work on genuinely interesting technical challenges, take ownership of production AI systems and help shape the AI capabilities of a growing business.