AI/ML Engineer

Brio Digital; Remote; GBP 75,000 - 100,000; Full time

Job summary

A leading AI consultancy is seeking a Senior Machine Learning Engineer specializing in Generative AI and LLM applications. In this fully remote role, you'll drive the architecture and productionization of advanced machine learning systems on GCP. The ideal candidate will have over 5 years of experience, strong Python skills, and familiarity with AI frameworks. Enjoy the autonomy of influencing technical direction while contributing to impactful projects within a collaborative team environment. Competitive salary up to £100k offered.

Benefits

High autonomy and ownership

Fully remote working

Opportunity to influence architecture

Qualifications

• 5+ years’ experience in machine learning engineering or applied AI roles.
• Experience with LLMs, Generative AI, and/or RAG-based systems.
• Strong Python skills using frameworks such as PyTorch, TensorFlow, or Hugging Face.

Responsibilities

• Design, develop, and deploy advanced machine learning models into production.
• Architect scalable LLMOps pipelines on GCP including fine-tuning.
• Collaborate with teams to translate business requirements into ML solutions.

Skills

Machine Learning Engineering

Generative AI

Python

GCP Vertex AI

Deep Learning

Statistical Modelling

Tools

PyTorch

TensorFlow

Hugging Face

Google GenAI

Docker

CI/CD

Git

Job description

Senior Machine Learning Engineer (Generative AI / LLMs)

Location: Fully Remote (UK-based)
Salary: £75,000 - £100,000 (depending on experience)

The Role

We're hiring a Senior Machine Learning Engineer to lead the design and productionisation 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 up to £100k, plus benefits.