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Staff ML Engineer | Agentic AI & Applied ML | London (Hybrid) | Contract | Inside IR35
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Staff ML Engineer | Agentic AI & Applied ML | London (3 days per week on-site) | Contract | Inside IR35
Location
Hybrid – London (3 days per week on-site)
Rate
Up to £1,500/day
Engagement
Contract – Inside IR35
We're supporting a major UK financial services organisation as they scale their AI engineering capability and accelerate the adoption of Generative AI and Agentic AI across the business.
We're looking for an exceptional Staff Machine Learning Engineer who combines deep applied ML expertise, outstanding hands-on engineering skills and proven technical influence across multiple teams.
This is a high-impact opportunity to help drive the organisation's UK AI agenda, building on established capabilities from its US operations while developing new solutions, engineering frameworks and use cases.
You'll remain deeply involved in coding and production delivery, leading through technical decisions, implementation and the standards you establish.
The opportunity
You'll play a central role in building and scaling enterprise AI capabilities, tackling increasingly complex applications where reliability, evaluation and sound engineering judgement are critical.
Working across multiple engineering teams, you'll establish reusable capabilities, solve difficult technical problems and raise the standard of AI delivery within a highly regulated environment.
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Key responsibilities
- Providing Staff-level technical leadership across Generative AI, LLM and Agentic AI initiatives.
- Designing, developing and productionising RAG, LLM and multi-agent solutions.
- Making critical decisions around model behaviour, evaluation, architecture, performance and scalability.
- Shaping reusable AI frameworks, tooling and engineering standards across multiple teams.
- Remaining deeply hands-on, leading implementation and resolving complex engineering challenges.
- Collaborating with senior technical stakeholders to challenge approaches and drive measurable business outcomes.
- Ensuring solutions meet demanding reliability, security and governance requirements throughout their production lifecycle.
What we're looking for
- Extensive hands-on Machine Learning Engineering experience, underpinned by strong applied ML and data science foundations.
- Deep understanding of model behaviour, probabilistic failure modes, evaluation and optimisation.
- Strong software engineering fundamentals, particularly Python, with recent, substantial production coding experience.
- A track record of personally delivering complex ML/AI systems through deployment, monitoring, scaling and ongoing operation.
- Deep practical expertise in LLMs, Generative AI, RAG and agentic architectures.
- Experience with AWS, MLOps and enterprise-scale AI infrastructure.
- Demonstrable Staff, Principal or equivalent impact: influencing technical direction, solving problems across teams and improving the effectiveness of other engineers.
- The ability to explain technical trade-offs clearly and connect engineering decisions with measurable outcomes.
- Strong judgement around AI governance, reliability and safe deployment.
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Depth and impact matter more than familiarity with a particular framework. Experience integrating LLM APIs or building RAG prototypes alone will not be sufficient; we're looking for someone who understands the underlying ML challenges and can engineer robust solutions at scale.
Experience within financial services or another highly regulated environment would be particularly beneficial.
Why consider this opportunity?
You'll take a leading technical role in an organisation making a significant investment in AI, influencing enterprise adoption and establishing capabilities used across the wider business.
We're particularly interested in engineers who can bring exceptional technical depth, cross-team influence and the ability to make an immediate contribution through hands-on delivery.
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