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Machine Learning Engineer
Brio Digital
- London, England, United Kingdom
- London, England, United Kingdom
Über
Direct message the job poster from Brio Digital
Senior Delivery Consultant at Brio Digital sourcing and placing across Brio Partners and Brio Logic. Location:
Fully Remote (UK-based)
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
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.
Seniority level Mid-Senior level
Employment type Full-time
Job function Engineering, Information Technology, and Consulting
Industries IT Services and IT Consulting, Business Consulting and Services, and Robotics Engineering
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- English
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