At a Glance
- Tasks: Transform research into impactful AI projects and collaborate with biologists.
- Company: Early-stage company revolutionising bio-analysis with AI automation tools.
- Benefits: Competitive salary, flexible hours, and a chance to work on groundbreaking technology.
- Other info: Dynamic environment with opportunities for innovation and growth.
- Why this job: Join a small team making a big impact at the intersection of AI and life sciences.
- Qualifications: Experience in ML/AI systems and strong Python skills required.
The predicted salary is between 60000 - 80000 £ per year.
We're hiring on behalf of an early-stage company building AI-powered automation tools for automating bio-analysis workflows. Their platform transforms complex, expert-led analytical processes into repeatable, AI-assisted workflows. It's a small team doing serious technical work at the intersection of AI and life sciences.
The Research Engineer owns the research function. You take a direction from product feedback and turn it into results, scoping, experiment design, implementation, data curation, and interpretation. You'll work closely with biologists, scientific contractors, and the broader team, and act as the technical sparring partner on what to build next.
What you'll do:
- Turn research directions into projects: scoping, experiment design, implementation, data, and results
- Define which metrics matter for agent system performance and which proxies are actually honest
- Build the evaluation infrastructure: benchmarks, harnesses, and the tooling around them
- Develop the research agent stack: memory, in-context learning, test-time compute, and models
- Fine-tune and post-train open models to improve agent performance
- Work with biologists, contractors, and annotators to build reproducible training and evaluation data pipelines
- Track what frontier labs are shipping and bring back what's relevant
Essential experience:
- Experience building ML/AI systems in a research-adjacent context, industry, lab, or PhD
- Experience building LLM-powered systems: prompts, context engineering, agent architectures
- Experience with evaluations and benchmarks, including tasks where 'correct' is ambiguous
- Familiarity with model training, including the data, optimisation, and evaluation work around it
- Strong engineering fundamentals, fluent in Python and comfortable across the AI/ML stack
- Rigorous approach to experiments: you think about confounds and can defend your results
- Experience with training and evaluation data pipelines, including reproducibility and observability
Nice to have:
- Background in a life science domain, biology, chemistry, medicine, or bioinformatics
- Post-training experience on LLMs
- Peer-reviewed publications or other settings where your ideas were stress-tested
- Open source contributions to scientific or AI tooling
Research Engineer (D in London employer: Hlx Life Sciences
Join an innovative early-stage company in London that is at the forefront of AI-powered automation in bio-analysis. As a Research Engineer, you'll be part of a small, dynamic team where your contributions directly impact the development of cutting-edge technology. The company fosters a collaborative work culture, offering ample opportunities for professional growth and the chance to work alongside experts in both AI and life sciences, making it an ideal environment for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Research Engineer (D in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to ML/AI systems. We want to see your work in action, so make it easy for potential employers to check out what you can do.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios relevant to research engineering. We recommend doing mock interviews with friends or using online platforms to get comfortable with the process.
✨Tip Number 4
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 are proactive and take the initiative to reach out directly.
We think you need these skills to ace Research Engineer (D in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Research Engineer role. Highlight any relevant projects or research you've done, especially those involving ML/AI systems.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about AI and life sciences. Share specific examples of how your background makes you a great fit for our team and the exciting work we do.
Showcase Your Technical Skills:Don’t shy away from detailing your technical expertise in Python and AI/ML. We want to see how you’ve applied these skills in real-world scenarios, so include any relevant projects or achievements.
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’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Hlx Life Sciences
✨Know Your Research Inside Out
Make sure you’re well-versed in the latest trends and breakthroughs in AI and life sciences. Familiarise yourself with the company’s projects and how they align with your experience. This will help you demonstrate your passion and knowledge during the interview.
✨Prepare for Technical Questions
Expect to dive deep into your technical skills, especially around ML/AI systems and Python. Brush up on your understanding of experiment design, data curation, and evaluation metrics. Be ready to discuss specific projects where you’ve applied these skills.
✨Showcase Collaboration Skills
Since this role involves working closely with biologists and contractors, be prepared to discuss your teamwork experiences. Share examples of how you’ve successfully collaborated on research projects and how you’ve acted as a technical partner in those settings.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company’s research direction, team dynamics, and future projects. This shows your genuine interest and helps you assess if the company is the right fit for you.
