At a Glance
- Tasks: Design AI evaluation frameworks and conduct experiments to improve insurance technology.
- Company: Join a cutting-edge AI company transforming the insurance industry.
- Benefits: Generous training budget, 33 days holiday, private healthcare, and equity options.
- Other info: Diverse and inclusive workplace with exceptional growth opportunities.
- Why this job: Make a real impact in AI while working with top talent in a dynamic environment.
- Qualifications: Experience in AI/ML, Python programming, and clear communication of technical findings.
The predicted salary is between 60000 - 80000 £ per year.
About Hyperexponential (hx)
At hyperexponential, we’re building the AI-powered platform that enables the world’s most critical decisions in a £7 trillion industry. Our platform brings together data, AI, and human expertise to give insurers the fastest path from submission to decision - helping them move faster, act smarter, and take on more risk with confidence.
About The HxAI Team
The Research Engine sits at the intersection of exploration and evidence-based decision-making. We ensure that major technical investments are de-risked through rigorous research before Engineering scales them into production. As a Research Engineer, you’ll bridge Product Management and Engineering by investigating emerging AI capabilities, validating technical approaches, and producing evidence that guides strategic product decisions.
What you’ll be doing:
- Design and maintain evaluation frameworks that enable consistent, automated measurement of AI agent performance across hundreds of insurance scenarios.
- Conduct structured technology assessments that evaluate emerging AI capabilities against specific product needs.
- Run disciplined experiments that decompose ambiguous research questions into testable hypotheses.
- Build comprehensive test suites covering actuarial edge cases, underwriting workflows, and pricing logic.
- Translate research findings into engineering action by identifying performance gaps and recommending technical approaches.
- Maintain domain fluency in insurance by staying current with actuarial concepts, underwriting practices, and pricing methodologies.
What you’ll need to have done:
- Worked on applied AI or ML problems where you had to structure your thinking, test hypotheses, and draw conclusions from messy or incomplete data.
- Had some exposure to evaluating AI or ML systems.
- Worked in or alongside production AI systems.
- Communicated technical findings clearly to non-technical audiences.
- Written Python comfortably across the AI/ML stack.
- Been part of cross-functional teams where research or analysis fed into real product or engineering decisions.
You’re unlikely to thrive here if:
- You prefer pure research environments with long timelines and academic publication goals.
- You need clearly defined problems with established methodologies.
- You view research as separate from implementation.
Compensation
At hx, we’re committed to salary transparency. Our approach is to design compensation that’s competitive in the market, fair across teams, and aligned with the impact our people make. Equity: We offer equity across all roles at hx.
Benefits:
- £5,000 training and conference budget for individual and group development.
- 25 days of holiday plus 8 bank holidays (33 days total).
- Company pension scheme via Penfold.
- Mental health support and therapy via Spectrum.life.
- Individual wellbeing allowance via Juno.
- Private healthcare insurance through AXA.
- Income protection and Life Insurance.
- Cycle to Work Scheme.
Additional Perks:
- Top-spec equipment (laptop, screens, adjustable desks, etc.).
- Regular remote and in-person hackathons, lunch and learns, socials, and game nights.
- Team breakfasts and lunches, snacks, drinks fridge, and a fun office.
- Exceptional opportunities for personal development and growth.
Interview process:
- Initial call with our Talent team (30 minutes).
- Meet the team (40 minutes).
- Take Home technical Assessment.
- Present the take-home live (1 hour).
- Values Interview with Two of our Leadership Team (60 minutes).
- Virtual/In-Person Coffee with our Senior Director of AI.
Our commitment to Diversity:
We know that progress depends on diverse perspectives, and we are committed to creating an environment where everyone can thrive, grow, and make an impact.
Next steps:
If this opportunity resonates with you, we encourage you to apply or share it with your connections! Our dedicated talent team reviews all applications, and we promise to provide feedback regardless of the outcome.
Research Engineer - AI Team employer: hyperexponential
At Hyperexponential, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. Our commitment to employee growth is evident through our generous training budget, comprehensive benefits, and a vibrant work environment that encourages creativity and teamwork. Located in a dynamic setting, we offer unique opportunities to make a tangible impact in the AI and insurance sectors, ensuring that every team member can thrive while contributing to groundbreaking advancements.
StudySmarter Expert Advice🤫
We think this is how you could land Research Engineer - AI Team
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Hyperexponential. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Prepare for your interviews by diving deep into AI and insurance topics. Show us you’re not just familiar with the tech but also understand how it impacts real-world decisions in the industry.
✨Tip Number 3
Practice explaining complex ideas simply. You’ll need to communicate your findings to non-technical folks, so being able to break down your research is key to impressing us.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step.
We think you need these skills to ace Research Engineer - AI Team
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Research Engineer role. Highlight your experience with AI and ML, and how it relates to the insurance industry. We want to see how your skills can directly impact our mission!
Showcase Your Problem-Solving Skills:In your application, give examples of how you've tackled ambiguous problems in the past. We love seeing candidates who can structure their thinking and draw conclusions from messy data, so don’t hold back on those stories!
Communicate Clearly:Remember, you’ll need to explain complex technical findings to non-technical folks. Use your application to demonstrate your ability to communicate clearly and effectively. We’re all about collaboration here at hx!
Apply Through Our Website:We encourage you to apply directly through our careers page. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find more info about us and other opportunities while you’re there!
How to prepare for a job interview at hyperexponential
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI and machine learning concepts. Be ready to discuss how you've approached ambiguity in past projects, structured your thinking, and tested hypotheses. This role is all about applying AI in real-world scenarios, so showing that you can navigate messy data will impress the interviewers.
✨Showcase Your Evaluation Skills
Prepare to talk about any experience you have with evaluating AI systems. Whether it's writing test suites or tracking model performance metrics, be specific about what you've done. They want to see that you understand the importance of evaluation frameworks and can think critically about why models might fail.
✨Communicate Clearly
You’ll need to translate complex technical findings into clear recommendations for non-technical audiences. Practice explaining your past projects in simple terms, focusing on the impact of your work. This will demonstrate your ability to bridge the gap between research and engineering, which is crucial for this role.
✨Be Ready for Real-World Applications
Familiarise yourself with the insurance industry and its complexities. Understand how your research can directly influence product decisions and improve engineering outcomes. Showing that you can connect your research to practical applications will set you apart from other candidates.
