Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join our team to automate and enhance machine learning processes in a cloud environment.
- Company: Markerstudy Group, a leading UK insurance provider with a collaborative culture.
- Benefits: Hybrid working, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact in the insurance industry using cutting-edge machine learning technology.
- Qualifications: Experience in data science or machine learning, with proficiency in Python and R.
- Other info: Dynamic role with excellent career advancement opportunities in a fast-paced environment.
The predicted salary is between 28000 - 38000 £ per year.
Locations: Manchester or Haywards Heath (hybrid working)
Role overview
Markerstudy Group has an exciting opportunity for a graduate machine learning engineer to fill out the automation, pipelining, DevOps, and modelling aspects of Markerstudy's market-leading technical modelling and pricing team. You will productionise novel insurance modelling processes as an automated machine learning pipeline within a cloud-based environment. Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1b. Most of Markerstudy's business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury's, O2, Halifax, AA, Saga and Lloyds Bank to list a few.
As a graduate machine learning engineer, you will work with and under the expert supervision of machine learning engineers to help build and maintain the pricing team's MLOps and ML Lifecycle environment and support the creation of pipelines by automating the sophisticated machine learning models and processes that underpin our market-leading technical modelling and pricing function.
Key Responsibilities:
- Build an MLOps / DevOps environment to support machine learning automation.
- Build the pipelines that automate the regular model update and monitoring processes.
- Work with the Technical Underwriting machine learning engineers to develop, implement, and maintain scalable processes and codebase that facilitate efficient business as usual in the Risk and Retail Pricing and Underwriting Teams.
- Work with the Technical Underwriting data scientists and analysts to implement and optimize new models and frameworks for production using traditional and bespoke MLOps toolkits.
Key Skills and Experience:
- Experience in data science, machine learning, or insurance risk or retail pricing.
- Experience in Azure ML or Databricks, or similar industry approved technology stack (i.e. AWS, Kubernetes and Docker, Google Cloud).
- Understanding of machine learning models and the modelling process, from data ingestion and cleaning to deployment and modelling – from the ground-up, not only through the use of packages and libraries.
- Advanced technical proficiency in Python and R and good understanding of best practices and coding standards for software development (i.e. SOLID principles, Agile methodology, etc.).
- Proficient at communicating results in a concise manner both verbally and written.
Behaviours:
- Collaborative and team player.
- Logical thinker with a professional and positive attitude.
- Passion to innovate and improve processes.
Graduate Machine Learning Engineer in Manchester employer: Vermelo
Contact Detail:
Vermelo Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Graduate Machine Learning Engineer in Manchester
✨Tip Number 1
Network like a pro! Reach out to professionals in the machine learning field on LinkedIn or at local meetups. Don’t be shy; ask for informational interviews to learn more about their experiences and get insider tips on landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to MLOps and automation. This is your chance to demonstrate your technical prowess and problem-solving abilities, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on common machine learning concepts and tools like Azure ML and Databricks. Practice explaining your thought process clearly and concisely, as communication is key in this role.
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining us. Tailor your application to highlight how your skills align with our needs, and don’t forget to follow up after applying to show your enthusiasm!
We think you need these skills to ace Graduate Machine Learning Engineer in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Graduate Machine Learning Engineer role. Highlight relevant experience in data science, machine learning, and any tools like Azure ML or Databricks that you’ve used. We want to see how your skills match 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 any specific projects or experiences that relate to the job description.
Showcase Your Technical Skills: Don’t forget to showcase your technical skills in Python and R. If you’ve worked on any projects involving MLOps or automation, make sure to include those details. We love seeing practical applications of your knowledge!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to submit all your documents in one go. Plus, it helps us keep track of your application!
How to prepare for a job interview at Vermelo
✨Know Your Tech Stack
Make sure you’re familiar with Azure ML, Databricks, and other relevant technologies mentioned in the job description. Brush up on your knowledge of MLOps and DevOps practices, as well as Python and R coding standards. Being able to discuss these tools confidently will show that you're ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare examples from your studies or projects where you’ve tackled complex problems using machine learning. Highlight how you approached the issue, the methods you used, and the outcomes. This will demonstrate your logical thinking and ability to innovate, which are key traits for this role.
✨Communicate Clearly
Practice explaining your technical projects in a way that’s easy to understand. You might be asked to describe your work to non-technical stakeholders, so being concise and clear is crucial. Use simple language to convey complex ideas, and don’t forget to prepare some questions to ask them too!
✨Emphasise Team Collaboration
Since this role involves working closely with other engineers and data scientists, be ready to discuss your experiences in team settings. Share examples of how you’ve collaborated on projects, resolved conflicts, or contributed to group success. This will highlight your ability to be a team player, which is essential for the collaborative environment at Markerstudy.