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- Tasks: Design and implement innovative machine learning solutions in the insurance industry.
- Company: Join a forward-thinking medium-sized organisation committed to advanced analytics.
- Benefits: Competitive salary, comprehensive benefits, and a collaborative work environment.
- Why this job: Make a real impact on exciting projects using cutting-edge technologies.
- Qualifications: Strong foundation in ML, experience with PyTorch, and proficiency in Python.
- Other info: Opportunity for career growth in a dynamic London 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'll 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.
This role focuses on training custom models, building robust ML pipelines, and deploying systems at scale from research experimentation through to monitored production services.
- 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.
A successful Machine Learning Engineer should have:
- 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 (eg 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 life cycle, 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're 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 - London employer: Michael Page Technology
Contact Detail:
Michael Page Technology Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer - London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can sometimes lead to job opportunities that aren't even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to audio processing or MLOps. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common ML concepts and frameworks like PyTorch. Practise explaining your past projects clearly, focusing on your problem-solving approach and results.
✨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 are proactive!
We think you need these skills to ace Senior Machine Learning Engineer - London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Senior Machine Learning Engineer. Highlight your experience with ML models, especially in audio processing, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Showcase Your Projects: Include specific examples of projects where you've designed and deployed ML solutions. If you've worked with PyTorch or built MLOps pipelines, let us know! This is your chance to shine and show us what you can bring to the table.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use straightforward language to describe your experience and skills. We appreciate a well-structured application that makes it easy for us to see your qualifications.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Don’t miss out on the chance to join our innovative team!
How to prepare for a job interview at Michael Page Technology
✨Know Your ML Fundamentals
Brush up on your machine learning and deep learning concepts. Be ready to discuss optimisation techniques and how they apply to real-world scenarios, especially in audio processing tasks like speaker diarization and ASR.
✨Showcase Your Hands-On Experience
Prepare to share specific examples of ML models you've trained and deployed. Highlight your experience with PyTorch or TensorFlow, and be ready to discuss the end-to-end ML pipelines you've built, including any MLOps tools you've used.
✨Demonstrate Your Problem-Solving Skills
Think of a few challenges you've faced in previous projects and how you overcame them. This role requires collaboration with product and business teams, so showing your ability to translate requirements into practical ML solutions will impress the interviewers.
✨Familiarise Yourself with the Company’s Tech Stack
Research the tools and technologies the company uses, such as Docker, Azure, and any specific ML frameworks. Being knowledgeable about their tech stack will show your genuine interest in the role and help you ask insightful questions during the interview.
