Machine Learning Engineer

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

Job summary

A leading technology firm is seeking a Senior Machine Learning Engineer to lead the design of Generative AI applications. The role involves developing and deploying machine learning models and influencing architectural decisions. Candidates should have 5+ years of experience and strong skills in Python, GCP Vertex AI, and LLMs. Join a remote team to work on impactful projects and enjoy a competitive salary up to £100k, plus benefits.

Benefits

Competitive salary

Fully remote work

High autonomy

Influence on architecture

Qualifications

• 5+ years’ experience in machine learning engineering or applied AI roles.
• Recent experience with LLMs and Generative AI.
• Strong Python skills using frameworks such as PyTorch or TensorFlow.

Responsibilities

• Design, develop, and deploy advanced machine learning models.
• Architect scalable LLMOps pipelines on GCP.
• Collaborate with teams to implement ML-driven solutions.

Skills

Experience with LLMs

Python

GCP Vertex AI

Machine learning engineering

Deep learning

Tools

PyTorch

TensorFlow

Hugging Face

Docker

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.