At a Glance
- Tasks: Build AI systems that enhance customer experiences and streamline processes.
- Company: An innovative AI-native Insurtech backed by top tech investors.
- Benefits: Competitive salary up to £160k, equity, bonuses, and a chance to shape the future.
- Other info: Be part of a dynamic team and help scale from 0 to 1.
- Why this job: Join at the ground level and make a real impact in people's lives.
- Qualifications: 2-7 years in applied Machine Learning with hands-on experience in startups.
The predicted salary is between 160000 - 160000 £ per year.
An AI-native Insurtech is hiring a Machine Learning Engineer. Backed by some of the best-known names in tech investing and already managing claims across $100M+ in premium for 30+ partners.
Timing — Join at the 0-to-1 stage and help build the engineering team and technical culture from the ground up.
Real impact — You'll ship ML that supports people during life's most critical moments, not dashboards no one uses.
Ownership — Work directly with founders, talk to customers, and own problems end to end as the company scales.
The Role
- Build AI systems that improve accuracy, speed up assessments, and lift the customer experience.
- Partner with domain specialists to turn messy, manual processes into reliable AI-driven workflows.
- Deploy machine learning solutions at scale, in production, where real money and real people depend on them.
- Help shape the engineering team and technical direction as one of the early hires.
- Learn — and help build — what it actually takes to scale a startup from 0 to 1.
What We're Looking For
- 2–7 years in applied Machine Learning, with ML products you've shipped at scale.
- You've built 0-to-1 inside a startup and can iterate fast under real constraints.
- Background at a hyperscaler, an AI-first startup, or big tech — or, if you're from a smaller/lesser-known company, a strong academic pedigree to match.
- Grounding in classical machine learning or LLM research.
- Hands-on experience building LLM-powered automation workflows.
- Strong Python for ML research and rapid prototyping.
- High agency you're happy to get in front of customers and stakeholders while you build, not just behind a screen.
Paying up to £160k + Equity + Bonus.
Machine Learning Engineer - AI Native Startup - up to £160k in London employer: We Source Talent
Join an innovative AI-native Insurtech as a Machine Learning Engineer, where you'll have the unique opportunity to shape the engineering team and technical culture from the ground up. With a focus on real impact, you'll deploy machine learning solutions that enhance customer experiences during critical moments, all while enjoying a collaborative work environment that fosters personal growth and offers competitive compensation, including equity and bonuses. This is your chance to be part of a dynamic startup at the forefront of technology, backed by leading investors and poised for significant growth.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer - AI Native Startup - up to £160k in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work at AI-native startups. Use platforms like LinkedIn to connect and engage with them. You never know who might have a lead on that perfect Machine Learning Engineer role!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's a GitHub repo or a personal website, make sure it highlights your experience with ML products and any cool automation workflows you've built. This will give you an edge when chatting with potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your past experiences in building ML systems and how you've tackled challenges. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both techies and non-techies.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight how your skills align with our mission of improving customer experiences through AI. Let's build something amazing together!
We think you need these skills to ace Machine Learning Engineer - AI Native Startup - up to £160k in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your applied Machine Learning experience and any relevant projects you've shipped at scale. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you're excited about this role and how your background aligns with our mission. Share specific examples of your work in AI and how you've contributed to building tech from the ground up.
Showcase Your Projects:If you've worked on any ML products or automation workflows, make sure to include them in your application. We love seeing real-world applications of your skills, so don’t hold back on sharing your achievements and the impact they had!
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at We Source Talent
✨Know Your ML Stuff
Make sure you brush up on your machine learning fundamentals. Be ready to discuss the projects you've worked on, especially those that involved deploying ML solutions at scale. They’ll want to hear about your hands-on experience and how you tackled real-world problems.
✨Show Your Startup Spirit
This role is all about building from the ground up, so highlight any experience you have in a startup environment. Talk about how you've iterated quickly under constraints and contributed to shaping a team or culture. They’re looking for someone who can thrive in a fast-paced setting.
✨Engage with Real Scenarios
Prepare to discuss how you would approach turning messy processes into reliable AI-driven workflows. Think of examples where you’ve improved accuracy or customer experience through your work. This shows you understand the impact of your role beyond just coding.
✨Be Ready to Collaborate
Since you'll be working closely with domain specialists and customers, demonstrate your ability to communicate effectively. Share experiences where you’ve collaborated with others to solve complex problems. They want to see that you can own issues end to end and engage with stakeholders confidently.
