Senior Machine Learning Engineer
Platform Recruitment
Cambridge, United Kingdom
yesterday
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
Senior Compensation
£ 120KJob location
Cambridge, United Kingdom
Tech stack
Artificial Intelligence
Amazon Web Services (AWS)
Azure
Cloud Computing
Continuous Integration
Information Engineering
Fraud Prevention and Detection
Python
Machine Learning
TensorFlow
Software Engineering
PyTorch
Scikit Learn
Kubernetes
Machine Learning Operations
Docker
Job description
- 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
Requirements
- 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
Benefits & conditions
We are a fast-growing FinTech/InsurTech company located in Cambridge, transforming how financial and insurance products are developed through machine learning and data-driven decision-making. Our platform utilizes advanced ML models for areas like fraud detection and risk modelling, enabling smarter decisions at scale. We offer a competitive salary range of £80,000-£120,000 plus bonus, flexible hybrid working arrangements, and a collaborative, engineering-first environment where you can have strong technical ownership and clear career progression opportunities.