2,765 Lead Machine Learning Engineer jobs in the United Kingdom

Lead Machine Learning Engineer

Up to £100,000

Company:

They are an AI-driven climate risk analytics platform that partners with businesses within Insurance, Private Equity, Asset Management and governments to understand and prepare for the physical and transitional impacts of climate change.

Responsibilities:

• Lead, mentor, and grow a high-performing team of ML engineers.
• Combine ML with physics-based risk models (flooding, tropical cyclones, wildfires) to deliver grounded, high-impact solutions.
• Establish gold-standard practices for evaluation, deployment, observability, and maintainability in ML model development.
• Turn complex technical challenges into clear business outcomes for colleagues and customers.

Requirements:

• MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields.
• 3+ years of experience in a Data Science, Data Analysis, or related role
• Strong hands-on experience with Python and SQL
• Excellent communication skills and stakeholder engagement ability
• Start-up mindset - thrives in lean, high-growth teams and rolls up sleeves to own problems end-to-end

Please note:

This role requires 3 days onsite per week onsite in London.

How to Apply:

Please register your interest by sending your CV to Emily Burgess via the Apply link on this page

Lead Machine Learning Engineer

Up to £100,000

Company:

They are an AI-driven climate risk analytics platform that partners with businesses within Insurance, Private Equity, Asset Management and governments to understand and prepare for the physical and transitional impacts of climate change.

Responsibilities:

• Lead, mentor, and grow a high-performing team of ML engineers.
• Combine ML with physics-based risk models (flooding, tropical cyclones, wildfires) to deliver grounded, high-impact solutions.
• Establish gold-standard practices for evaluation, deployment, observability, and maintainability in ML model development.
• Turn complex technical challenges into clear business outcomes for colleagues and customers.

Requirements:

• MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields.
• 3+ years of experience in a Data Science, Data Analysis, or related role
• Strong hands-on experience with Python and SQL
• Excellent communication skills and stakeholder engagement ability
• Start-up mindset - thrives in lean, high-growth teams and rolls up sleeves to own problems end-to-end

Please note:

This role requires 3 days onsite per week onsite in London.

How to Apply:

Please register your interest by sending your CV to Emily Burgess via the Apply link on this page

• Lead the design, development, training, and deployment of machine learning models and algorithms.
• Architect and build scalable ML pipelines and infrastructure to support large-scale data processing and model serving.
• Mentor and guide a team of machine learning engineers, fostering a culture of innovation and technical excellence.
• Collaborate with data scientists, software engineers, and product managers to identify opportunities for ML application and define project roadmaps.
• Evaluate and select appropriate ML frameworks, tools, and technologies.
• Optimize model performance, efficiency, and reliability in production environments.
• Conduct research into state-of-the-art ML techniques and evaluate their applicability to business problems.
• Implement MLOps best practices for model versioning, deployment, monitoring, and retraining.
• Ensure the ethical and responsible application of machine learning models.
• Contribute to the development of internal ML libraries and platforms.
• Communicate complex technical concepts and results to both technical and non-technical audiences.
• Drive technical strategy and roadmap for machine learning initiatives.

• Master's or PhD in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related quantitative field.
• 5+ years of hands-on experience in machine learning engineering, with at least 2 years in a leadership or mentoring capacity.
• Strong proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
• Deep understanding of various ML algorithms, statistical modeling, and data mining techniques.
• Proven experience in deploying and maintaining ML models in production (MLOps).
• Excellent understanding of software engineering best practices, including version control (Git) and CI/CD.
• Strong analytical and problem-solving skills.
• Exceptional leadership, communication, and interpersonal skills.
• Experience with containerization technologies (Docker, Kubernetes) is a plus.
• Familiarity with natural language processing (NLP) or computer vision is advantageous.

• Leading the design, development, and deployment of machine learning models and algorithms for various applications.
• Overseeing the entire ML lifecycle, from data gathering and preparation to model training, evaluation, and deployment.
• Mentoring and guiding a team of machine learning engineers, fostering a collaborative and high-performance environment.
• Developing and implementing scalable and efficient ML pipelines and infrastructure.
• Collaborating with data scientists, software engineers, and product managers to integrate ML solutions into products and services.
• Staying abreast of the latest advancements in machine learning research and applying them to real-world challenges.
• Ensuring the quality, reliability, and performance of deployed ML models.
• Contributing to the technical roadmap and strategy for AI/ML initiatives.
• Evaluating and selecting appropriate tools, technologies, and frameworks for ML development.
• Communicating complex technical concepts to both technical and non-technical stakeholders.

• Designing, building, and deploying robust and scalable machine learning models and systems.
• Leading and mentoring a team of ML engineers, providing technical guidance and fostering best practices.
• Collaborating with data scientists, software engineers, and product managers to define ML roadmaps and implement solutions.
• Researching and evaluating new ML technologies, algorithms, and tools to improve model performance and efficiency.
• Developing and maintaining CI/CD pipelines for ML models, ensuring smooth deployment and monitoring.
• Optimizing ML models for performance, scalability, and cost-effectiveness.
• Contributing to the overall software architecture and design of ML-powered products.
• Staying current with the latest advancements in machine learning and artificial intelligence.
• Documenting ML processes, models, and systems effectively.

• Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.
• 5+ years of experience in machine learning engineering, with a proven track record of delivering production-ready ML systems.
• Strong proficiency in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn.
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools.
• Solid understanding of statistical modeling, data mining, and various ML algorithms (e.g., supervised, unsupervised, deep learning).
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Excellent problem-solving, analytical, and debugging skills.
• Strong leadership and communication skills, with the ability to mentor junior engineers.
• Experience in developing and deploying models in a cloud environment.

Lead Machine Learning Engineer

Up to £100,000

Company:

They are an AI-driven climate risk analytics platform that partners with businesses within Insurance, Private Equity, Asset Management and governments to understand and prepare for the physical and transitional impacts of climate change.

Responsibilities:

• Lead, mentor, and grow a high-performing team of ML engineers.
• Combine ML with physics-based risk models (flooding, tropical cyclones, wildfires) to deliver grounded, high-impact solutions.
• Establish gold-standard practices for evaluation, deployment, observability, and maintainability in ML model development.
• Turn complex technical challenges into clear business outcomes for colleagues and customers.

Requirements:

• MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields.
• 3+ years of experience in a Data Science, Data Analysis, or related role
• Strong hands-on experience with Python and SQL
• Excellent communication skills and stakeholder engagement ability
• Start-up mindset - thrives in lean, high-growth teams and rolls up sleeves to own problems end-to-end

Please note:

This role requires 3 days onsite per week onsite in London.

How to Apply:

Please register your interest by sending your CV to Emily Burgess via the Apply link on this page

At Zego, we know that traditional motor insurance holds good drivers back. It’s too complicated, too expensive, and it doesn't take into account how well you actually drive. 

That’s why, since 2016, we’ve been on a mission to change all of that. Our mission at Zego is to offer the lowest priced insurance for good drivers.

From van drivers and gig workers to everyday car drivers, our customers are our driving force — they’re at the heart of everything we do.

We’ve sold tens of millions of policies so far, and raised over $200 million in funding. And we’re only just getting started.

Who we're looking for

We are looking for a Lead Machine Learning Engineer to play a key role in our Core Pricing team. You will drive innovation by optimising and automating Pricing processes to enable faster, more accurate decision-making. Your work will focus on developing and maintaining tooling and frameworks that enhance the efficiency of our predictive models, reducing deployment times, increasing scalability, and improving model performance through regular updates and monitoring. You will work closely with our Data Scientists, Actuaries, and Product team to deliver scalable, production-grade ML systems.

Key Responsibilities

• Build model lifecycle tooling (deployment, monitoring and alerting) for our predictive models (for example claims cost, conversion, retention, market models)
• Maintain and improve the development environment (Kubeflow) used by our Data Scientists and Actuaries
• Develop and maintain pricing analytics tools that enable faster impact assessments, reducing manual work
• Collaborate with the technical pricing, street pricing and product teams to gather requirements and feedback on tooling and to build impactful technology
• Communicate complex concepts to technical and non-technical stakeholders through clear storytelling

Required Skills

• Education: Bachelor’s or Master’s degree in Statistics, Data Science, Computer Science or related field
• Experience: Proven experience in ML model lifecycle management
• Core Competencies :
• Model lifecycle: You’ve got hands-on experience with managing the ML model lifecycle, including both online and batch processes
• Statistical Methodology: You have worked with GLMs and other machine learning algorithms and have in-depth knowledge of how they work
• Python: You have built and deployed production-grade Python applications and you are familiar with data science libraries such as pandas and scikit-learn
• Tooling & Environment :
• DevOps: You have experience working with DevOps tooling, such as gitops, Kubernetes, CI/CD tools (we use buildkite) and Docker
• Cloud: You have worked with cloud-based environments before (we use AWS)
• SQL: You have a good grasp of SQL, particularly with cloud data warehouses like Snowflake
• Version control: You are proficient with git
• Soft Skills:  
• You are an excellent communicator, with an ability to translate non-technical requirements into clear, actionable pieces of work
• You have proven your project management skills, with the ability to manage multiple priorities
• You have worked closely together in cross-functional teams, including with Data Scientists, Actuaries, and Product Managers

Nice To Have

• Experience in UK motor insurance
• Telematics Data: Familiarity with behavioural driving data and its application in insurance pricing
• Understanding of pricing modelling tools such as Akur8 or Emblem
• Experience with IaC (we use Terraform)
• Experience with gRPC/protobuf

What’s it like to work at Zego?

Joining Zego is a career-defining move. People go further here, reaching their full potential to achieve extraordinary things. 

We’re spread throughout the UK and Europe, and united by our drive to get things done. We’re proud of our company and our culture – a friendly and inclusive space where we can lift each other up and celebrate our wins every day.

Together, we’re setting the bar higher, delivering exceptional work that makes a difference. Our people are the most important part of our story, and everyone here plays a role. There’s loads of room to learn and grow, and you’ll get the freedom to steer your career wherever you want.

You’ll work alongside a talented group who embrace each other's differences and aren’t afraid of a challenge. We recognise our achievements, learn from our mistakes, and help each other to be the best we can be. Together, we’re making insurance matter. 

How we work

We believe that teams work better when they have time to collaborate and space to get things done. We call it Zego Hybrid. We ask you to spend at least one day a week in our central London office. We think it’s a good mix of collaborative face time and flexible home-working, setting us up to achieve the right balance between work and life.

Our approach to AI

We believe in the power of AI to meaningfully improve how we work - helping us move faster, think differently, and focus on what matters most. At Zego, we encourage people to stay curious and intentional about how AI is leveraged in their work and teams to drive practical impact every day. This is your chance to do the most meaningful work of your career - and we’ll provide you with the tools, support, and freedom to do it well.

Benefits

We reward our people well. Join us and you’ll get a market-competitive salary, private medical insurance, company share options, generous holiday allowance, and a whole lot of wellbeing benefits. We also offer an annual flexible hybrid working contribution, which you can use to support with your travel to the office or towards your own personal development. And that’s just for starters.

There’s more to Zego than just a job - Check out our blog for insights, stories, and more.

We’re an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, marital status, or disability status.

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