AI/ML Engineer

Brio Digital; Remote; GBP 80,000 - 100,000; Full time

Job summary

A leading technology company is seeking a Senior Machine Learning Engineer to lead the design and production of Generative AI and LLM applications. This role offers a chance to work with GCP and deliver scalable systems while collaborating with product teams. Ideal candidates have over 5 years in machine learning and experience with LLMs or Generative AI. This is a fully remote position, providing high autonomy and influence over project direction.

Benefits

High autonomy

Collaborative team environment

Opportunity for real impact

Qualifications

• 5+ years’ experience in machine learning engineering or applied AI roles.
• Demonstrable experience with LLMs, Generative AI, and RAG-based systems.
• Strong Python skills using modern ML frameworks.

Responsibilities

• Design and deploy advanced machine learning models into production.
• Architect scalable LLMOps pipelines.
• Collaborate with teams to translate business requirements into ML solutions.

Skills

Machine Learning Engineering

Generative AI

LLMs

Python

GCP Vertex AI

Tools

PyTorch

TensorFlow

Hugging Face

Docker

Job description

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