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- Tasks: Develop and deploy cutting-edge AI models for audio processing and agentic systems.
- Company: Innovative insurance company leveraging advanced analytics and machine learning.
- Benefits: Competitive salary, comprehensive benefits, and a collaborative work environment.
- Why this job: Make a real impact in the insurance industry with the latest AI technologies.
- Qualifications: Strong ML foundation, experience with PyTorch, and end-to-end ML pipeline skills.
- Other info: Exciting opportunity for career growth in a dynamic London-based team.
The predicted salary is between 80000 - 100000 £ per year.
Work on Cutting-Edge AI & Agentic Systems. End-to-End Ownership & Impact.
About Our Client
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.
Job Description
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.
The Successful Applicant
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 (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.
What's on Offer
- 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.
Machine Learning Engineer, AI Engineer, Machine Learning Engineer, Deep Learning Engineer, Generative AI Engineer, NLP Engineer, Speech AI Engineer, Audio ML Engineer, Agentic AI Engineer, AI Solutions Engineer, AI Platform Engineer, Applied AI Engineer, in London employer: Page Personnel
Contact Detail:
Page Personnel Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer, AI Engineer, Machine Learning Engineer, Deep Learning Engineer, Generative AI Engineer, NLP Engineer, Speech AI Engineer, Audio ML Engineer, Agentic AI Engineer, AI Solutions Engineer, AI Platform Engineer, Applied AI Engineer, in London
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even local tech events. The more people you know, the better your chances of landing that dream job.
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those related to machine learning and AI. Share your GitHub repos or any cool demos you've built. This is your chance to shine and show potential employers what you can do!
✨Ace the Interview
Prepare for technical interviews by brushing up on your ML concepts and coding skills. Practice common interview questions and maybe even do mock interviews with friends. Confidence is key, so get comfortable talking about your experience!
✨Apply Through Us!
Don't forget to check out our website for the latest job openings. Applying through us not only gives you access to great opportunities but also helps you stand out in the application process. Let's get you that job!
We think you need these skills to ace Machine Learning Engineer, AI Engineer, Machine Learning Engineer, Deep Learning Engineer, Generative AI Engineer, NLP Engineer, Speech AI Engineer, Audio ML Engineer, Agentic AI Engineer, AI Solutions Engineer, AI Platform Engineer, Applied AI Engineer, in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your hands-on experience with ML models, especially in audio processing tasks, as this will catch our eye!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about AI and how your background aligns with our needs. Share specific examples of projects you've worked on that relate to the role.
Showcase Your Projects: If you’ve got any personal or professional projects that demonstrate your skills in building ML pipelines or deploying models, make sure to mention them! We love seeing practical applications of your work.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any updates!
How to prepare for a job interview at Page Personnel
✨Know Your Models Inside Out
Make sure you can discuss the machine learning models you've worked with in detail. Be prepared to explain how you trained, evaluated, and deployed them, especially if they relate to audio processing tasks like ASR or speaker diarization.
✨Showcase Your MLOps Skills
Highlight your experience with end-to-end ML pipelines and MLOps tools. Be ready to talk about specific projects where you used tools like MLflow or Docker, and how you ensured reliability and scalability in your deployments.
✨Demonstrate Collaboration
Since this role involves working with both technical and non-technical teams, prepare examples of how you've effectively communicated complex ML concepts to diverse audiences. This will show that you can bridge the gap between tech and business needs.
✨Prepare for Technical Questions
Expect to face technical questions related to PyTorch, TensorFlow, and the Hugging Face ecosystem. Brush up on your Python skills and be ready to solve problems on the spot, as practical assessments are common in these interviews.
