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Senior Machine Learning Engineer

Lorien·London (South East England)Senior
Salary not stated
Vox Summary
  • Role Responsibilities: Lead end-to-end machine learning projects, applying scientific reasoning, designing experiments, working with real operational data, and integrating solutions into wider systems.
  • Key Requirements: Proven senior-level ML experience, strong mathematics and statistics background, excellent Python skills, experience with real-world data, and ability to evaluate models with structured experimentation.
  • Conditions & Skills: Operate autonomously in a secure, regulated environment, communicate technical ideas clearly, and demonstrate strong software engineering practices and data ethics understanding.
  • Tools & Technologies: Experience with Python, experiment tracking tools like Weights & Biases, AWS services such as SageMaker and Bedrock, and adaptable to evolving AI development platforms.
  • Work Environment: The role is on-site in London, requiring a senior practitioner capable of independent ownership and outcome-focused work in a high-regulation context.
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Job description

Senior Machine Learning EngineerApplying rigorous machine learning to real-world problems that matter 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. Where strong market solutions exist, they are used. 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. This means the work is thoughtful, challenging, and purposeful, rather than driven by novelty or trend. What you'll be doingYou'll take ownership of complex ML problems, applying scientific thinking and pragmatism in equal measure. You will: • 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 forThis role suits a senior ML practitioner who values judgement, evidence, and outcomes over theoretical or tooling purity. Essential experience: • 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 encounterThe environment evolves, but typical tools include: • 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. Adaptability and outcome focus matter more than platform allegiance. 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. If interested, apply now! Guidant, Carbon60, Lorien & SRG - The Impellam Group Portfolio are acting as an Employment Business in relation to this vacancy.

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Original source
reed.co.uk
Posted
Jun 18, 2026 · true date
Last verified
2 hours ago
Quality score
35/100
Salary stated0
Company identified0
applyUrl0
postedAt15
Complete description20

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