At a Glance
- Tasks: Transform research ideas into impactful AI projects and collaborate with scientists.
- Company: Early-stage company revolutionising bio-analysis with AI-powered automation tools.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Dynamic work environment with a focus on innovation and collaboration.
- Why this job: Join a small team at the forefront of AI and life sciences, making a real difference.
- 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 (Research) 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. With a strong emphasis on collaboration, employee growth, and a culture that values scientific inquiry, this role offers a unique opportunity to work at the intersection of AI and life sciences while enjoying the vibrant atmosphere of London.
StudySmarter Expert Advice🤫
We think this is how you could land Research Engineer (Research) 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. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨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
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 are proactive about their job search!
We think you need these skills to ace Research Engineer (Research) 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, as this will catch our eye!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and life sciences, and how your background makes you a perfect fit for our team. Be genuine and let your personality come through.
Showcase Your Projects:If you've worked on any interesting projects, especially those related to LLMs or bioinformatics, make sure to mention them. We love seeing practical applications of your skills, so don’t hold back!
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
Before the interview, dive deep into the company's focus on AI-powered automation tools for bio-analysis. Familiarise yourself with their platform and think about how your past experiences align with their needs. Be ready to discuss specific projects you've worked on that relate to their work.
✨Prepare for Technical Questions
Expect to be quizzed on your experience with ML/AI systems and LLM-powered systems. Brush up on your Python skills and be prepared to explain your approach to experiment design and data curation. Practising coding problems or discussing your thought process on past projects can really help.
✨Showcase Collaboration Skills
Since you'll be working closely with biologists and contractors, highlight your teamwork experience. Think of examples where you acted as a technical partner or contributed to cross-disciplinary projects. This will demonstrate your ability to communicate complex ideas effectively.
✨Ask Insightful Questions
At the end of the interview, have some thoughtful questions ready. Inquire about their current research challenges or how they measure success in their projects. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you.
