Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead the design and delivery of cutting-edge ML systems for real-time predictions.
- Company: Join a mission-driven company focused on simplifying financial decision-making for everyone.
- Benefits: Enjoy hybrid working, generous holidays, private healthcare, and more perks tailored to you.
- Why this job: Be part of an inclusive culture that celebrates creativity and innovation in AI engineering.
- Qualifications: Extensive experience in ML systems, strong Python skills, and a collaborative mindset required.
- Other info: Opportunity to influence ML tooling and work with talented teams in a supportive environment.
The predicted salary is between 48000 - 84000 £ per year.
Join to apply for the Staff Machine Learning Engineer role at Compare the Market
1 day ago Be among the first 25 applicants
Join to apply for the Staff 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!
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!
As a Staff Machine Learning Engineer, you’ll play a pivotal role in designing, scaling, and evolving the machine learning infrastructure that powers Compare the Market’s most ambitious AI products. From LLM-based personalisation to real-time optimisation systems, you’ll help define how models are developed, deployed, and maintained in production—reliably and responsibly. This is a high-impact, hands-on leadership role. You’ll work across product, data science, and engineering to lead delivery of complex ML systems. You’ll also define the core MLOps capabilities for the business and establish the standards and patterns that accelerate safe, scalable AI deployment across teams.
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:
ML Systems Design & Delivery
- Lead the architecture and delivery of ML systems that power real-time and batch predictions at scale
- Design production pipelines for training, deployment, and monitoring using modern MLOps tooling
- Take ownership of technical quality, resilience, and observability of critical ML services
- Build reusable tools and frameworks to enable fast, safe experimentation and deployment
Platform, Standards & MLOps Foundations
- Define and build the core MLOps capabilities for the organisation, including training pipelines, deployment frameworks, and observability tooling
- Establish standardised patterns and best practices to accelerate model development, testing, and deployment
- Lead the evolution of our ML platform, working with engineering partners to improve scalability, governance, and developer experience
- Contribute to responsible ML practices—supporting auditability, explainability, and model health monitoring
Technical Leadership & Collaboration
- Partner with data scientists to take models from prototype to production with clear interfaces and robust engineering
- Lead cross-team technical design sessions and architectural reviews
- Provide mentorship, pair programming, and code reviews for other engineers across the AI function
Innovation & Culture
- Stay ahead of developments in MLOps, LLM infrastructure, and AI engineering best practices
- Influence long-term strategic direction for ML tooling and delivery across the organisation
- Help build a high-performing, inclusive, and collaborative ML Engineering culture
What we’d like to see from you:
- Extensive experience designing and deploying ML systems in production
- Deep technical expertise in Python and modern ML tooling (e.g. MLflow, TFX, Airflow, Kubeflow, SageMaker, Vertex AI)
- Experience with infrastructure-as-code and CI/CD practices for ML (e.g. Terraform, GitHub Actions, ArgoCD)
- Proven ability to build reusable tooling, scalable services, and resilient pipelines for real-time and batch inference
- Strong understanding of ML system lifecycle: testing, monitoring, governance, observability
- Excellent collaboration and communication skills; able to influence cross-functional teams and lead complex technical work
- A background in software engineering, computer science, or a quantitative field—or equivalent experience leading ML systems in production
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!
Seniority level
-
Seniority level
Mid-Senior level
Employment type
-
Employment type
Full-time
Job function
-
Job function
Engineering and Information Technology
-
Industries
Software Development
Referrals increase your chances of interviewing at Compare the Market by 2x
Get notified about new Machine Learning Engineer jobs in London Area, United Kingdom .
London, England, United Kingdom 2 weeks ago
London, England, United Kingdom 1 week ago
London, England, United Kingdom 2 weeks ago
London, England, United Kingdom 1 month ago
London, England, United Kingdom 2 days ago
London, England, United Kingdom 19 hours ago
London, England, United Kingdom 2 weeks ago
London, England, United Kingdom 1 week ago
London, England, United Kingdom 2 weeks ago
London, England, United Kingdom 1 month ago
Graduate Software Engineer – ML Data Platform
Machine Learning Scientists and Engineers: AI for Quantum
London, England, United Kingdom 2 months ago
London, England, United Kingdom 2 days ago
London, England, United Kingdom 1 month ago
London, England, United Kingdom 5 months ago
London, England, United Kingdom 5 months ago
London, England, United Kingdom 5 months ago
London, England, United Kingdom 2 weeks ago
London, England, United Kingdom 4 weeks ago
London, England, United Kingdom £50,000.00-£60,000.00 1 month ago
Machine Learning Engineer – Search and Recommendation
London, England, United Kingdom 1 month ago
London, England, United Kingdom 4 days ago
London, England, United Kingdom 2 weeks ago
Graduate Software Engineer 2025 – RegTech
London, England, United Kingdom 2 weeks ago
Greater London, England, United Kingdom 4 weeks ago
London, England, United Kingdom 5 days ago
We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr
Staff Machine Learning Engineer employer: Compare the Market
Contact Detail:
Compare the Market Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Machine Learning Engineer
✨Tip Number 1
Familiarise yourself with the latest MLOps tools and practices mentioned in the job description, such as MLflow, TFX, and Kubeflow. Being able to discuss these technologies confidently during your interview will demonstrate your readiness for the role.
✨Tip Number 2
Showcase your experience with Python and CI/CD practices by preparing examples of past projects where you successfully implemented these skills. This will help you illustrate your technical expertise and problem-solving abilities.
✨Tip Number 3
Prepare to discuss how you've collaborated with cross-functional teams in previous roles. Highlight specific instances where your communication skills led to successful project outcomes, as this is crucial for the collaborative culture at StudySmarter.
✨Tip Number 4
Stay updated on the latest trends in AI and machine learning, particularly around LLM infrastructure. Being knowledgeable about current developments will not only impress your interviewers but also show your passion for the field.
We think you need these skills to ace Staff Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your extensive experience in designing and deploying ML systems. Emphasise your technical expertise in Python and modern ML tooling, as well as any relevant projects that showcase your skills.
Craft a Compelling Cover Letter: In your cover letter, express your passion for machine learning and how it aligns with the company's mission. Mention specific examples of your previous work that relate to the responsibilities outlined in the job description, such as leading architectural design or building reusable tools.
Showcase Collaboration Skills: Highlight your collaboration and communication skills in your application. Provide examples of how you've influenced cross-functional teams or led complex technical projects, as these are key aspects of the role.
Demonstrate Continuous Learning: Mention any recent courses, certifications, or self-directed learning you've undertaken in MLOps, AI engineering best practices, or related fields. This shows your commitment to staying ahead in the rapidly evolving tech landscape.
How to prepare for a job interview at Compare the Market
✨Showcase Your ML Expertise
Be prepared to discuss your extensive experience in designing and deploying machine learning systems. Highlight specific projects where you've successfully implemented ML solutions, focusing on the tools and frameworks you used.
✨Demonstrate Technical Leadership
Since this role involves leading cross-team technical design sessions, be ready to share examples of how you've influenced technical decisions in previous roles. Discuss your approach to mentoring and collaborating with data scientists and engineers.
✨Understand MLOps Practices
Familiarise yourself with modern MLOps tooling and practices, such as CI/CD for ML. Be prepared to explain how you've implemented these in past projects, particularly focusing on infrastructure-as-code and deployment frameworks.
✨Emphasise Collaboration Skills
This role requires excellent collaboration and communication skills. Think of examples where you've successfully worked with cross-functional teams to deliver complex ML systems, and be ready to discuss how you can influence and lead within a team.
