AI/ML Engineer (Generative AI / LLMs)
Location: Fully Remote (UK-based)
The Role
We’re hiring a Senior Machine Learning Engineer to lead the design and production of Generative AI and Large Language Model (LLM) applications. This role sits at the heart of an AI-focused engineering team, delivering scalable, production-grade systems using GCP and Google’s AI ecosystem.
You’ll be a senior, hands-on engineer owning complex technical problems end to end, with a strong influence over architecture, tooling, and the future direction of LLM-powered products.
What You’ll Be Doing
* Design, develop, and deploy advanced machine learning and deep learning models into production.
* Architect scalable LLMOps pipelines on GCP / Vertex AI, including fine-tuning, vector search, and low-latency inference.
* Build end-to-end LLM applications, leveraging RAG (Retrieval-Augmented Generation), agentic workflows, and prompt engineering.
* Implement robust evaluation frameworks to monitor LLM quality, hallucinations, token usage, and content safety.
* Develop and deploy autonomous or semi-autonomous agents using modern agent frameworks and Google AI tooling.
* Collaborate with product and engineering teams to translate complex business requirements into ML-driven solutions.
* Monitor, optimise, and continuously improve models in live production environments.
* Contribute to the architecture and evolution of the AI platform and supporting data infrastructure.
* Stay current with emerging research, tools, and best practices across ML and Generative AI.
What We’re Looking For
Essential
* 5+ years’ experience in machine learning engineering or applied AI roles.
* Recent, demonstrable experience with LLMs, Generative AI, and/or RAG-based systems.
* Strong Python skills using frameworks such as PyTorch, TensorFlow, Hugging Face, or Google GenAI.
* Experience with vector databases and retrieval-based architectures.
* Proven experience designing and operating large-scale ML systems in production.
* Strong experience with GCP Vertex AI (or equivalent cloud ML platforms).
* Solid software engineering fundamentals: APIs, Docker, CI/CD, and Git.
* Strong understanding of deep learning, statistical modelling, and optimisation techniques.
Nice to Have
* Experience with agentic design patterns (e.g. ReAct, Chain-of-Thought, tool use).
* Familiarity with LLM evaluation frameworks such as RAGAS or TruLens.
* Experience fine-tuning large models or working with reinforcement learning techniques.
* Background in mathematics, statistics, or theoretical computer science.
* Understanding of data governance, bias mitigation, or model interpretability.
Why Join
* Work on real, production-grade GenAI systems with clear business impact.
* High autonomy and ownership in a senior, hands-on engineering role.
* Fully remote working with a collaborative, distributed team.
* Opportunity to influence architecture and long-term technical direction.
* Competitive salary