Senior Machine Learning Engineer

• Design, build, and deploy machine learning models for fraud detection, risk scoring, and predictive analytics
• Develop scalable ML pipelines and work closely with data engineering teams
• Collaborate with product and domain experts to translate business problems into ML solutions
• Optimise model performance and ensure reliability in production environments
• Contribute to architecture and best practices across ML and MLOps

Technologies:

• AI
• AWS
• Azure
• CI/CD
• Cloud
• Docker
• GCP
• Kubernetes
• Machine Learning
• PyTorch
• Python
• TensorFlow

• 4+ years experience in machine learning or AI roles
• Strong Python skills, with experience in frameworks such as PyTorch, TensorFlow, or Scikit-learn
• Experience deploying ML models into production, including MLOps, CI/CD, Docker, and Kubernetes
• Solid understanding of statistics, data modelling, and software engineering principles
• Experience with cloud platforms such as AWS, GCP, or Azure
• Exposure to financial services or insurance domains is advantageous, but not essential

We are a fast-growing FinTech/InsurTech company in Cambridge, transforming how financial and insurance products are built using machine learning and data-driven decision-making. Our platform leverages advanced ML models to power fraud detection, risk modelling, underwriting optimisation, and customer analytics, enabling smarter and faster decisions at scale. With strong investment and a product-led engineering culture, we offer a high-impact environment, competitive salary of £80,000-£120,000 plus bonus, flexible hybrid working with a Cambridge-based office, and clear progression with the opportunity to influence ML strategy.