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- Tasks: Build and deploy machine learning models to revolutionise the insurance industry.
- Company: Join Artificial, a pioneering tech company transforming specialty insurance.
- Benefits: Enjoy private medical insurance, generous holidays, and stock options.
- Why this job: Make a real impact in a collaborative environment with cutting-edge technology.
- Qualifications: Fluency in Python ML stack and experience in deploying ML models.
- Other info: Be part of a diverse team committed to innovation and growth.
The predicted salary is between 36000 - 60000 £ per year.
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.
Responsibilities
- 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
Qualifications
- 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.
Machine Learning Engineer employer: Artificial Labs
Contact Detail:
Artificial Labs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at Artificial. A friendly chat can sometimes lead to opportunities that aren’t even advertised!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those that demonstrate your ability to work with messy data or build models from scratch. This will give you an edge when discussing your experience.
✨Tip Number 3
Prepare for the interview by brushing up on your Python ML stack knowledge. Be ready to explain your past projects and how they relate to the responsibilities at Artificial. Confidence in your expertise can really make you stand out!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the Artificial team. Let’s make it happen!
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the Machine Learning Engineer role. Highlight your experience with Python ML stacks and any relevant projects you've worked on. We want to see how you can add value to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for insurtech and how your skills align with our mission at Artificial. Let us know why you're excited about the opportunity to make an impact in the specialty insurance market.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled complex data challenges in the past. We love candidates who can demonstrate their ability to work with messy, real-world data and explain model outputs to non-technical users.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, we love seeing applications come in through our own platform!
How to prepare for a job interview at Artificial Labs
✨Know Your ML Stack
Make sure you’re well-versed in the Python ML stack, especially tools like scikit-learn, PyTorch, and TensorFlow. Brush up on your knowledge of how to build and ship ML models to production, as this will likely come up during technical discussions.
✨Showcase Problem-Solving Skills
Prepare to discuss specific examples where you've tackled messy, real-world data. Be ready to explain how you identified opportunities for ML to add value and the impact your solutions had on previous projects.
✨Communicate Effectively
Since you'll need to explain model outputs to non-technical users, practice simplifying complex concepts. Think about how you can convey your ideas clearly and concisely, as communication is key in a collaborative environment.
✨Demonstrate Curiosity and Ownership
Artificial values curiosity and continuous learning, so be prepared to discuss how you stay updated with industry trends and technologies. Share instances where you took ownership of a project or initiative, showcasing your proactive nature.
