Machine Learning Engineer

Machine Learning Engineer

There’s a big difference between an LLM demo and an AI system you can trust in production.

This role is about building the latter.

We’re working with an established organisation building production GenAI systems from the ground up — and they’re looking for an ML Engineer who wants ownership beyond the model.

You’ll build RAG systems, AI agents, copilots and intelligent document workflows, then solve the engineering challenges that come with actually putting them into production.

Think:

• LLMs, RAG & agentic workflows
• Evaluation, hallucination mitigation & guardrails
• Embeddings, vector search & retrieval
• Production Python and backend engineering
• GCP / Vertex AI
• APIs, Docker, CI/CD & monitoring
• Building AI systems that are scalable, observable and reliable

The interesting part is the ownership. You won’t just be plugging into a mature AI platform - you’ll help shape the patterns, tooling and architecture for how GenAI gets built and deployed across the organisation.

We’re looking for someone who has already taken LLM/GenAI applications into production and enjoys the engineering problems that appear once the prototype works.