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- Tasks: Design and implement innovative machine learning solutions in the insurance industry.
- Company: Join a forward-thinking medium-sized organisation in London.
- Benefits: Competitive salary, comprehensive benefits, and a collaborative work environment.
- Why this job: Make a real impact with cutting-edge technologies on exciting projects.
- Qualifications: Strong foundation in machine learning and hands-on experience with ML models.
- Other info: Opportunity for career growth in a dynamic and innovative setting.
The predicted salary is between 80000 - 100000 £ per year.
Join the analytics team as a Machine Learning Engineer in the insurance industry, where you will design and implement innovative machine learning solutions. This permanent role in London offers an exciting opportunity to work on impactful projects in a forward-thinking environment.
This opportunity is with a medium-sized organisation in the insurance industry. The company is committed to utilising advanced analytics and machine learning to enhance its services and deliver value to its clients.
Responsibilities- Design, train, and optimise machine learning models for audio processing tasks such as speaker diarization, automatic speech recognition (ASR), and voice activity detection.
- Build and maintain training and inference pipelines using PyTorch and related ML frameworks.
- Source, curate, and prepare training datasets; implement preprocessing, augmentation, and validation workflows.
- Run structured experiments, evaluate model performance, and iterate based on measurable results.
- Build, deploy, and operate end-to-end MLOps pipelines, including experiment tracking, model versioning, and production monitoring.
- Package and deploy models using Docker and cloud infrastructure, with a focus on reliability and scalability.
- Design and deploy agent-based AI systems that can execute multi-step workflows and integrate with external tools.
- Build Model Context Protocol (MCP) servers to enable standardised integration between models, APIs, and data sources.
- Evaluate and integrate large language models into production systems where they add clear value.
- Collaborate with product and business teams to translate requirements into practical ML solutions.
- Strong foundation in machine learning, deep learning, and optimisation.
- Hands-on experience training, evaluating, and deploying ML models in real-world systems.
- Proficiency with PyTorch (preferred) or TensorFlow; familiarity with the Hugging Face ecosystem.
- Experience with audio or speech models and frameworks.
- Experience building and maintaining end-to-end ML pipelines and MLOps tooling (e.g. MLflow, Weights & Biases, DVC, or similar).
- Strong Python skills; experience with Docker, CI/CD, and cloud platforms (Azure preferred).
- Practical experience designing agentic AI systems and integrating models with external services.
- Comfortable owning the full ML lifecycle, from data preparation to production deployment.
- Clear communicator who can work effectively across technical and non-technical teams.
- Competitive salary ranging from £80,000 to £100,000 per annum.
- Comprehensive benefits package to support your well-being.
- Opportunity to work in a leading organisation within the insurance industry.
- Collaborative and innovative work environment in London.
- Chance to work on impactful projects using the latest technologies.
If you are a passionate Machine Learning Engineer looking to make a difference in the insurance industry, we encourage you to apply and be part of this exciting opportunity in London.
Senior Machine Learning Engineer in City of London employer: Michael Page
Contact Detail:
Michael Page Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer in City of London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. This is your chance to shine and demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common ML questions and practical scenarios. We want you to feel confident and ready to tackle any challenge they throw your way!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing passionate candidates like you!
We think you need these skills to ace Senior Machine Learning Engineer in City of London
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 PyTorch, MLOps, and any relevant projects you've worked on. We want to see how your skills align 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 team. Be sure to mention specific projects or experiences that relate to the insurance industry.
Showcase Your Projects: If you've worked on any cool machine learning projects, make sure to showcase them! Whether it's through a portfolio or links to GitHub, we love seeing practical applications of your skills. It gives us a better idea of what you can bring to the table.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're serious about joining our innovative team at StudySmarter!
How to prepare for a job interview at Michael Page
✨Know Your ML Models Inside Out
Make sure you can discuss your experience with machine learning models in detail. Be prepared to explain how you've designed, trained, and optimised models, especially for audio processing tasks. This will show your depth of knowledge and hands-on experience.
✨Showcase Your MLOps Skills
Since the role involves building and maintaining end-to-end MLOps pipelines, be ready to talk about your experience with tools like MLflow or Weights & Biases. Highlight any projects where you've implemented CI/CD practices or worked with Docker and cloud platforms.
✨Prepare for Technical Questions
Expect technical questions that test your understanding of PyTorch, TensorFlow, and the Hugging Face ecosystem. Brush up on key concepts and be ready to solve problems on the spot, as this demonstrates your practical skills and ability to think critically.
✨Communicate Clearly and Collaboratively
This role requires collaboration with both technical and non-technical teams. Practice explaining complex concepts in simple terms, and be prepared to discuss how you've successfully worked across different teams in the past. Good communication is key!
