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For Companies At a Glance
- Tasks: Design and deploy cutting-edge machine learning models for fraud detection and predictive analytics.
- Company: Fast-growing FinTech/InsurTech company in Cambridge with a product-led culture.
- Benefits: Competitive salary, bonus, hybrid work, and opportunities for professional growth.
- Other info: Dynamic environment with strong investment and excellent career advancement opportunities.
- Why this job: Join a team transforming financial products with innovative machine learning solutions.
- Qualifications: Experience in machine learning, strong Python skills, and familiarity with MLOps.
The predicted salary is between 80000 - 120000 £ per year.
Join a fast-growing FinTech/InsurTech company in Cambridge that is transforming how financial and insurance products are built using machine learning and data-driven decision-making. Their platform leverages advanced ML models to power areas such as 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, they are looking for a Senior Machine Learning Engineer to play a key role in building and deploying production-grade ML systems.
The Role:
- 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.
Key Skills:
- 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 machine learning algorithms and techniques.
Senior Machine Learning Engineer employer: Platform Recruitment
Contact Detail:
Platform Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the FinTech and InsurTech space, especially those who are already working with machine learning. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to fraud detection or risk modelling. This is your chance to demonstrate your expertise beyond the CV.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and familiarising yourself with frameworks like PyTorch and TensorFlow. Practice coding challenges and be ready to discuss your past projects in detail.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Machine Learning Engineer role. Highlight your experience with machine learning models, Python skills, and any relevant projects you've worked on. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how you can contribute to our mission at StudySmarter. Be sure to mention specific skills or experiences that relate directly to the job description.
Showcase Your Projects: If you've worked on any interesting ML projects, make sure to include them in your application. Whether it's a personal project or something from a previous job, we love seeing practical examples of your work and how you approach problem-solving.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates about your application status. Plus, it shows you're keen on joining our team!
How to prepare for a job interview at Platform Recruitment
✨Know Your ML Models Inside Out
Make sure you can discuss the machine learning models you've worked with in detail. Be prepared to explain how you designed, built, and deployed them, especially in production environments. Highlight your experience with frameworks like PyTorch or TensorFlow, and be ready to share specific examples of how your models improved business outcomes.
✨Showcase Your Collaboration Skills
Since this role involves working closely with product and domain experts, demonstrate your ability to collaborate effectively. Prepare examples of past projects where you translated complex business problems into ML solutions, and how you communicated technical concepts to non-technical stakeholders.
✨Be Ready for Technical Challenges
Expect some technical questions or challenges during the interview. Brush up on your Python skills and be familiar with MLOps practices, CI/CD pipelines, and containerisation tools like Docker and Kubernetes. Practising coding problems related to ML can also give you an edge.
✨Understand the Company’s Vision
Research the company’s mission and how they leverage machine learning in their products. Being able to articulate how your skills align with their goals will show your genuine interest in the role. Think about how you can contribute to their vision of transforming financial and insurance products through data-driven decision-making.