Machine Learning Engineer

Artificial Labs Ltd
London

About Artificial

Help shape the future of specialty insurance

At Artificial, we’re building the next generation of technology for the specialty (re)insurance market. Our mission is to transform how brokers and carriers operate in complex markets by removing operational barriers and enabling smarter, faster decision-making.

We use modern technology to solve real challenges for some of the world’s leading brokers and insurers. By automating the repetitive and structuring the complex, we help our partners unlock new opportunities for innovation and growth.

You’ll be joining a collaborative team that values curiosity, ownership, and continuous learning. We work in an environment where ideas are heard, support is built-in, and outcomes matter. Everyone here has the chance to make a tangible impact on our products, our customers, and the industry.

We've just raised $45M (£33M) in Series B funding from lead investor CommerzVentures, new investor Move Capital, as well as all existing shareholders. This investment round gives us the room to grow with confidence, continue to innovate, and ensure that Artificial remains the first choice for brokers and carriers seeking a smarter way to trade digitally.

Join us, and take the chance to be a part of something that will change the landscape of insurance for generations.

About the role

  • Identify where ML can add the most value and make the case for it

  • Build ML models (ranking, prediction, recommendations) to power platform insights

  • Design and maintain ML infrastructure: feature stores, model serving, monitoring

  • Collaborate with engineering to integrate models into the platform

About you

  • You're fluent in the Python ML stack (e.g. scikit-learn, PyTorch/TensorFlow, pandas/Polars)

  • You've designed, built and shipped ML models to production

  • You can work with messy, sparse, real-world data

  • You can explain model outputs to non-technical users

  • You know when a model is good enough to ship

  • You're proactive, self-directed and comfortable being part of a small, autonomous team

  • Bonus: you know a bit of Haskell (our core platform is written in it)

We especially want to hear from you if you have
  • Collaborative skills with an emphasis on product quality.

  • Experience in insurtech, insurance or related industries.

  • Strong problem-solving skills.

  • Experience in a distributed work environment.

Benefits

  • Private medical insurance

  • Income protection insurance

  • Life insurance of 4 * base salary

  • On-site gym and shower facilities

  • Enhanced maternity and paternity pay

  • Team social events and company parties

  • Salary exchange on pension and nursery fees

  • Access to Maji, the financial wellbeing platform

  • Company stock options managed through Ledgy

  • Milestone Birthday Bonus and a Life Events leave policy

  • Generous holiday allowance of 28 days plus national holidays

  • Home office and equipment allowance, and a company MacBook

  • Learning allowance and leave to attend conferences or take exams

  • YuLife employee benefits, including EAP and bereavement helplines

  • For each new hire, we plant a tree through our partnership with Ecologi Action

  • The best coffee machine in London, handmade in Italy and imported just for us!

    We’re proud to be an equal opportunities employer and are committed to building a team that reflects the diverse communities around us. If there’s anything you need to make the hiring process more accessible, just let us know—we’re happy to make adjustments. You’re also welcome to share your preferred pronouns with us at any point.

    Think you don’t meet every requirement? Please apply anyway. We value potential as much as experience, and we know that raw talent counts.

    As part of our hiring process, we’ll carry out some background checks. These may include a criminal record check, reviewing your credit history, speaking with previous employers and confirming your academic qualifications.

Posted 2026-02-04

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