About this role
Salary: £80,000 - 120,000 per year
Requirements: 4+ years experience in machine learning or AI rolesStrong Python skills, with experience in frameworks such as PyTorch, TensorFlow, or Scikit-learnExperience deploying ML models into production, including MLOps, CI/CD, Docker, and KubernetesSolid understanding of statistics, data modelling, and software engineering principlesExperience with cloud platforms such as AWS, GCP, or AzureExposure to financial services or insurance domains is advantageous, but not essential Responsibilities: Design, build, and deploy machine learning models for fraud detection, risk scoring, and predictive analyticsDevelop scalable ML pipelines and work closely with data engineering teamsCollaborate with product and domain experts to translate business problems into ML solutionsOptimise model performance and ensure reliability in production environmentsContribute to architecture and best practices across ML and MLOps Technologies: AIAWSAzureCI/CDCloudDockerGCPKubernetesMachine LearningPyTorchPythonTensorFlow More:
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.
last updated 29 week of 2026