Senior Machine Learning Engineer - AI in London

We're looking for a Senior Machine Learning Engineer to join a multidisciplinary data and AI team delivering high-impact, real-world solutions in a secure and highly regulated environment. This is a senior, hands-on practitioner role, not a people-management position. You'll operate with a high degree of autonomy, leading complex machine learning work end-to-end through technical depth, sound judgement, and delivery credibility.

The organisation is outcome-led rather than technology-led. Machine learning is built in-house only where problems are genuinely complex, niche, or sensitive - requiring experimentation, evaluation, and iteration beyond what can be bought.

What you'll be doing:

• Take ownership of complex ML problems, applying scientific thinking and pragmatism in equal measure.
• Lead end-to-end machine learning delivery, from problem definition through experimentation, evaluation, and iteration.
• Apply mathematical, statistical, and scientific reasoning to form hypotheses, quantify uncertainty, and interpret results.
• Design and run structured experiments to assess model behaviour, performance, and user impact.
• Work with real, imperfect operational data, not just curated or static datasets.
• Collect, assess, and transform data to support model evaluation and continuous improvement.
• Balance rigour with pragmatism, delivering solutions that are robust, proportionate, and fit for purpose.
• Integrate machine learning components into wider systems, considering performance, reliability, and operational constraints.
• Communicate complex technical ideas clearly to non-technical stakeholders, enabling informed decision-making.
• Engage confidently in deep technical design and review discussions with peers.
• Operate effectively within a strong technical assurance and review culture.
• Collaborate with internal teams and selected external partners working at the leading edge of AI.

What we're looking for:

• Proven experience operating at senior practitioner level as a Machine Learning Engineer, AI Engineer, Applied ML Scientist, or equivalent.
• Strong grounding in applied mathematics, statistics, and scientific practice.
• Demonstrated ability to evaluate ML models using quantitative evidence and structured experimentation.
• Excellent Python skills for building, evaluating, and iterating on ML solutions.
• Experience working with real-world, imperfect data from operational systems.
• Strong software engineering practices, including readable, maintainable, and well-tested code.
• Experience integrating ML components into broader production systems.
• Clear understanding of data ethics, privacy, and responsible use of data.
• Strong communication skills across technical and non-technical audiences.
• Proven ability to lead work independently and take ownership of outcomes.

Technologies you'll encounter:

• Python for experimentation, modelling, and evaluation.
• Weights & Biases (or equivalent) for experiment tracking.
• AWS, including services such as SageMaker and Bedrock.
• Internally supported AI development platforms and tooling.

This role is not suited to candidates who are dogmatic about specific tools.

Desirable experience:

• Working in secure, safety-critical, or heavily regulated environments.
• Background in sectors such as energy, oil & gas, defence, or public sector.
• Experience within formal technical assurance or governance processes.
• Collaboration with external suppliers, partners, or research organisations.
• Comfort operating at pace where quality, safety, and compliance are non-negotiable.

If you enjoy solving complex problems, applying scientific thinking to messy reality, and delivering ML that stands up to scrutiny, this role offers both challenge and meaning.