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- Tasks: Lead a team to build and maintain machine learning systems for personalisation and optimisation.
- Company: Join Compare the Market, a company dedicated to simplifying financial decision-making for everyone.
- Benefits: Enjoy hybrid working, generous holidays, private healthcare, and development opportunities.
- Why this job: Be part of a creative culture that values collaboration and celebrates wins while driving AI innovation.
- Qualifications: Experience in leading ML engineering teams and deploying scalable ML systems is essential.
- Other info: We welcome diverse skills and experiences; you don’t need to tick every box to apply.
The predicted salary is between 54000 - 84000 £ per year.
Job Description – Machine Learning Engineering Manager (006298)
Job Description
Machine Learning Engineering Manager – ( 006298 )
Description
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!
We change lives by making it simple to switch and save money and that’s why good things happen when you meerkat.
We’d love you to be part of our journey!
We’re scaling our AI capabilities at Compare the Market, and Machine Learning Engineering is at the core of how we turn models into production-ready systems. As a Machine Learning Engineering Manager, you’ll lead a team of MLEs responsible for building, deploying, and maintaining the ML infrastructure that powers our personalisation, optimisation, and intelligent decision-making products.
This is a hybrid role for a hands-on engineering leader—someone who can lead people, deliver at pace, and contribute to system design and platform standards. You’ll partner with data science, analytics, and platform engineering teams to accelerate how AI is developed and deployed across the organisation.
Everyone is welcome!
We have a culture of creativity. We approach our work passionately, improve constantly and celebrate our wins at every turn. We are an inclusive workplace and our employees are comfortable bringing their authentic, whole selves to work. Everyone is welcome. Be you.
This means we’re excited to hear from people with a range of skills, experiences and ideas. We don’t expect you to tick all the boxes, but would love to hear what makes you great for this role.
Some of the great things you’ll do:
Team Leadership & Delivery
• Lead a team of MLEs delivering robust, scalable machine learning systems into production
• Drive team planning, estimation, and sprint delivery—ensuring projects are delivered on time and to a high standard
• Support the development of real-time and batch ML workflows across a variety of business use cases
• Collaborate closely with data scientists to move prototypes into high-quality production systems
Platform & Engineering Standards
• Contribute to the design and evolution of our internal ML platform and tooling
• Champion best practices in CI/CD, observability, reproducibility, and infrastructure-as-code for ML
• Ensure all deployed systems meet requirements for resilience, testing, security, and performance
• Influence and contribute to shared frameworks, libraries, and deployment pipelines
Strategy & Cross-Functional Collaboration
• Work with technical and product leads to align team roadmaps to business goals
• Identify and unblock cross-team dependencies involving data science, platform, and software engineering
• Help shape platform direction by feeding back requirements from applied ML delivery
People & Culture
• Line manage and mentor MLEs, supporting their career development and technical growth
• Foster a culture of collaboration, feedback, and continuous improvement
• Lead hiring, onboarding, and team capability development initiatives
What we’d like to see from you:
• Experience leading engineering teams focused on machine learning, data platforms, or applied AI delivery
• Proven track record deploying ML systems in production at scale (batch and/or real-time)
• Strong technical background in Python and ML engineering tooling (e.g. MLflow, Airflow, SageMaker, Vertex AI, Databricks)
• Understanding of infrastructure-as-code and CI/CD for ML systems (e.g. Terraform, GitHub Actions, ArgoCD)
• Ability to lead delivery in agile environments—balancing scope, prioritisation, and quality
• Excellent communication and collaboration skills across technical and non-technical stakeholders
• A background in software engineering, MLOps, or data engineering with production ML experience
Nice to have:
• Familiarity with streaming or event-driven ML architectures (e.g. Kafka, Flink, Spark Structured Streaming)
• Experience working in regulated domains such as insurance, finance, or healthcare
• Exposure to large language models (LLMs), vector databases, or RAG pipelines
• Experience building or managing internal ML platforms, experimentation frameworks, or feature stores
There’s something for everyone.
We’re a place of opportunity. You’ll have the tools and autonomy to drive your own career, supported by a team of amazingly talented people.
And then there’s our benefits. 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!
#LI-HL1
Primary Location
Primary Location
: United Kingdom
Other Locations
Other Locations
: United Kingdom
Work Locations
Work Locations
: London – Shoreditch White Collar Factory 1 Old Street Yard, Shoreditch London EC1Y 8AF
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Machine Learning Engineering Manager employer: BGL Group
Contact Detail:
BGL Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineering Manager
✨Tip Number 1
Familiarise yourself with the latest trends in machine learning and AI, especially those relevant to financial services. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the machine learning and engineering fields. Attend industry meetups or webinars to connect with potential colleagues and learn more about the company culture at Compare the Market.
✨Tip Number 3
Prepare to discuss your leadership style and how you've successfully managed teams in the past. Be ready to share specific examples of how you've driven projects to completion and fostered a collaborative environment.
✨Tip Number 4
Brush up on your technical skills, particularly in Python and ML engineering tools mentioned in the job description. Being able to demonstrate your hands-on experience with these technologies can set you apart from other candidates.
We think you need these skills to ace Machine Learning Engineering Manager
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning and team leadership. Use specific examples of projects where you've deployed ML systems in production, and mention any tools or technologies that align with the job description.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how it aligns with the company's mission. Discuss your leadership style and how you foster collaboration and continuous improvement within teams. Be sure to mention any unique skills or experiences that make you a great fit for this role.
Showcase Technical Skills: Clearly outline your technical expertise in Python and ML engineering tools. If you have experience with CI/CD practices or infrastructure-as-code, be sure to include that as well. Providing concrete examples of how you've used these skills in past roles will strengthen your application.
Highlight Cross-Functional Collaboration: Demonstrate your ability to work with diverse teams by providing examples of successful collaborations with data scientists, product leads, or other stakeholders. This will show that you can effectively bridge the gap between technical and non-technical teams, which is crucial for this role.
How to prepare for a job interview at BGL Group
✨Showcase Your Leadership Skills
As a Machine Learning Engineering Manager, you'll be leading a team. Be prepared to discuss your leadership style and provide examples of how you've successfully managed teams in the past. Highlight your experience in mentoring and developing talent.
✨Demonstrate Technical Proficiency
Make sure to brush up on your technical skills, especially in Python and ML engineering tools like MLflow or SageMaker. Be ready to discuss specific projects where you've deployed ML systems in production, focusing on the challenges you faced and how you overcame them.
✨Understand Cross-Functional Collaboration
This role requires working closely with data scientists and other technical teams. Prepare to talk about your experience in cross-functional collaboration, how you align team goals with business objectives, and any strategies you've used to unblock dependencies.
✨Emphasise Continuous Improvement
The company values a culture of feedback and improvement. Be ready to share examples of how you've fostered a culture of collaboration and continuous learning within your teams. Discuss any initiatives you've led that contributed to team development and performance enhancement.
