Lead Machine Learning Engineer London, England, United Kingdom

Zego
London
2 weeks ago
Applications closed

Related Jobs

View all jobs

Lead Machine Learning Engineer

Senior Machine Learning Engineer

Data Science Consultant

Data Scientist

Principal Data Scientist London, United Kingdom

Lead Software Engineer (Machine Learning)

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.

#LI-IL1

#LI-Hybrid


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.