Machine Learning Engineer

Edison Smart®
London
4 weeks ago
Create job alert

Machine Learning Engineer - Contract (Financial Services, Outside IR35)

Duration: 6 months

Rate: £650 - £750 per day

IR35: Outside

Location: UK / Remote


We’re seeking an experienced Machine Learning Engineer to support a Financial Services organisation on an initial 6-month contract, working on production-grade ML systems that operate in regulated, high-volume environments.

This role is ideal for someone comfortable taking models from research through to deployment, with a strong appreciation for robust engineering, governance, and scalability.


Responsibilities

  • Design, build, and deploy machine learning models into production within a Financial Services environment
  • Collaborate closely with Data Scientists, Software Engineers, Risk, and Product teams
  • Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring)
  • Ensure models meet requirements around performance, resilience, and explainability
  • Contribute to MLOps best practices, model governance, and technical standards
  • Support model monitoring, drift detection, and ongoing optimisation


Required Experience

  • Proven commercial experience as a Machine Learning Engineer, ideally within Financial Services, FinTech, or a regulated environment
  • Strong Python skills and hands-on experience with ML libraries (TensorFlow, PyTorch, scikit-learn)
  • Experience deploying and supporting ML models in production
  • Solid understanding of data pipelines, versioning, testing, and software engineering best practices
  • Experience working with cloud platforms (AWS, GCP, or Azure)


Nice to Have

  • Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases
  • Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.)
  • Docker and Kubernetes experience
  • Exposure to model governance, explainability, or regulatory frameworks


Contract Details

  • £650–£750 per day (Outside IR35)
  • Initial 6-month contract, with strong extension potential
  • Immediate or short-notice start preferred

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.