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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 authenticity and celebrates wins together.
- Qualifications: Experience in leading ML engineering teams and deploying systems at scale is essential.
- Other info: We're looking for diverse skills and experiences—don't hesitate to apply even if you don't tick every box!
The predicted salary is between 43200 - 72000 £ 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 #J-18808-Ljbffr
Machine Learning Engineering Manager (London) employer: BGL Group
Contact Detail:
BGL Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineering Manager (London)
✨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, particularly those who have experience in leading teams. Attend industry meetups or webinars to connect with potential colleagues and learn about their experiences.
✨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 team environment.
✨Tip Number 4
Research Compare the Market's current machine learning initiatives and be prepared to discuss how your skills and experiences align with their goals. Showing that you understand their mission can set you apart from other candidates.
We think you need these skills to ace Machine Learning Engineering Manager (London)
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, especially in agile environments.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how it aligns with the company's mission. Mention your experience with Python and ML engineering tools, and how you can contribute to their ML platform and culture.
Showcase Leadership Skills: Emphasise your experience in leading teams and mentoring engineers. Provide examples of how you've fostered collaboration and continuous improvement within your teams, as this is crucial for the role.
Highlight Cross-Functional Collaboration: Discuss your ability to work with various stakeholders, including data scientists and product leads. Share instances where you've successfully aligned team goals with business objectives, showcasing your strategic thinking.
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, particularly in delivering machine learning projects.
✨Demonstrate Technical Proficiency
Make sure you can talk confidently about your technical background, 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.
✨Understand the Business Context
Familiarise yourself with Compare the Market's mission and how machine learning plays a role in their products. Showing that you understand the business goals will demonstrate your ability to align your team's work with the company's objectives.
✨Prepare for Collaboration Questions
Since this role involves working closely with data scientists and other teams, be ready to discuss how you've collaborated across different functions. Share examples of how you've resolved conflicts or unblocked dependencies in previous roles.
