Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop and optimise Machine Learning products while collaborating with data scientists and tech teams.
- Company: Join Compare the Market, a company dedicated to simplifying financial decision-making for everyone.
- Benefits: Enjoy hybrid working, generous holiday allowance, private healthcare, and paid development days.
- Why this job: Be part of an innovative team driving impactful ML solutions in a supportive environment.
- Qualifications: Proficiency in Python, SQL, R, and understanding of ML algorithms and MLOps practices required.
- Other info: Entry-level position with opportunities for career growth and skill development.
The predicted salary is between 28800 - 48000 £ per year.
Join to apply for the Machine Learning Engineer role at Compare the Market Join to apply for the Machine Learning Engineer role at Compare the Market Our purpose is to make great financial decision making a breeze for everyone, and that purpose drives us every day. It’s why we’re on a mission to create an automated quoting engine, with the simplest of experiences, wrapped in a brand everyone loves! As a Machine Learning Engineer, you will be working closely with data scientists and wide range of business and tech stakeholders with varying levels of understanding towards Machine Learning, and will identify the tech requirements to productionise automated, scalable and stable Machine Learning products integrated into production systems that deliver actions and / or actionable insights. Develop, maintain, monitor (health & performance) and optimise integrated Machine Learning products Work closely with Data Engineering, Platform and Architecture teams to improve and develop new products, integrations, tools and technologies Work with data scientists to productionise various ML models, making sure the code follows best practice; Follow best practice for the management and interrogation of large scale ‘structured’ and ‘unstructured’ datasets (million+ rows with thousand+ features, policy documents, etc) Enable the collection of new data and the refinement of existing data sources. Help manage day to day operations of the Data Science & Analytics platform (Databricks), and other ML Solutions built & operated tech across various platforms. Coordination and management of small to medium sized machine learning projects in small cross functional squads Strong understanding of a wide range of ML algorithms Understanding of MLOps practices for managing and monitoring models in production. Proficiency in programming languages such as Python, SQL and R. Knowledge of SQL and NoSQL databases for data storage and retrieval. Strong software engineering skills, including version control (Git), code reviews, and unit testing. Familiarity with common data science libraries and tools (e.g., Experience in setting up and managing continuous integration and continuous deployment pipelines. AWS, GCP, Azure) for model deployment and data management. You’ll have the tools and autonomy to drive your own career, supported by a team of amazingly talented people. For us, it’s not just about a competitive salary and hybrid working, we care about what matters to you. From a generous holiday allowance and private healthcare to an electric car scheme and paid development, wellbeing and CSR days, we’ve pretty much got you covered! Seniority level Entry level Employment type Full-time Job function Engineering and Information Technology Industries Software Development Get notified about new Machine Learning Engineer jobs in London Area, United Kingdom . Data Scientist – AI / ML, Python, Scripting, Cyber Security Graduate Software Engineer – ML Data Platform We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI. #
Machine Learning Engineer Language employer: Compare the Market
Contact Detail:
Compare the Market Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer Language
✨Tip Number 1
Familiarise yourself with the specific machine learning algorithms mentioned in the job description. Understanding these algorithms will not only help you during interviews but also demonstrate your genuine interest and knowledge in the field.
✨Tip Number 2
Engage with the community by participating in relevant forums or attending meetups focused on machine learning and data science. This can help you network with professionals in the industry and may even lead to referrals for the position.
✨Tip Number 3
Showcase any personal projects or contributions to open-source projects that involve machine learning. Having tangible examples of your work can set you apart from other candidates and provide talking points during interviews.
✨Tip Number 4
Brush up on your programming skills, particularly in Python, SQL, and R. Being proficient in these languages is crucial for the role, and demonstrating your coding abilities can significantly boost your chances of landing the job.
We think you need these skills to ace Machine Learning Engineer Language
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, programming languages like Python and SQL, and any projects that demonstrate your understanding of MLOps practices. Customise it to reflect the skills mentioned in the job description.
Craft a Compelling Cover Letter: In your cover letter, express your passion for machine learning and how it aligns with Compare the Market's mission. Mention specific projects or experiences that showcase your ability to work with data scientists and manage ML products.
Showcase Technical Skills: Clearly outline your proficiency in programming languages, data management tools, and any experience with cloud platforms like AWS, GCP, or Azure. Provide examples of how you've applied these skills in previous roles or projects.
Highlight Team Collaboration: Since the role involves working closely with various stakeholders, emphasise your experience in cross-functional teams. Share examples of successful collaborations and how you contributed to project outcomes.
How to prepare for a job interview at Compare the Market
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in programming languages like Python, SQL, and R. Bring examples of projects where you've implemented machine learning algorithms and how you managed data using SQL and NoSQL databases.
✨Understand MLOps Practices
Familiarise yourself with MLOps practices, as this role requires managing and monitoring models in production. Be ready to explain how you would set up continuous integration and deployment pipelines for machine learning models.
✨Demonstrate Collaboration Skills
Since you'll be working closely with data scientists and various stakeholders, highlight your experience in cross-functional teams. Share examples of how you've successfully coordinated small to medium-sized machine learning projects.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities, especially regarding optimising integrated machine learning products. Think of scenarios where you've had to troubleshoot or improve the performance of a model or system.
