At a Glance
- Tasks: Design and build AI solutions for drug discovery, impacting real-world health outcomes.
- Company: Fast-growing life sciences tech organisation focused on innovative drug discovery.
- Benefits: Career development, collaborative culture, and exposure to cutting-edge molecular AI tools.
- Other info: Collaborative environment with opportunities for professional growth and innovation.
- Why this job: Make a tangible impact on drug discovery while working at the intersection of science and technology.
- Qualifications: PhD or equivalent experience in molecular AI or computational chemistry; strong Python skills required.
The predicted salary is between 36000 - 60000 £ per year.
This role is for AI research engineers who want to design, build, and productionise cutting-edge AI solutions for drug discovery. You will develop advanced models to predict molecular properties (ADMET, potency, binding) using deep learning and physics-based approaches, integrating them into production-grade software used daily by chemists. Your work will have a tangible impact on real-world drug programmes, influencing experimental decisions, accelerating project timelines, and reducing dead ends in discovery.
The client is a fast-growing life sciences technology organisation applying AI to accelerate drug discovery across oncology, dementia, inflammation, and global health. They specialise in turning curated, non-public experimental molecular property data into actionable insights for chemists. The company values collaboration, scientific rigour, and ownership, creating a culture where engineers can shape the technological framework from inception and work at the intersection of chemistry, biology, physics, and machine learning.
Key responsibilities- Design, develop, and productionise molecular property prediction models using deep learning and physics-based approaches.
- Integrate advanced algorithms into core platform services for chemists, ensuring scalability, performance, and reliability.
- Build and maintain software interfaces, APIs, and distributed systems supporting AI-driven workflows.
- Support internal and external users by understanding workflows, gathering feedback, and translating scientific needs into actionable product improvements.
- Collaborate closely with engineers, scientists, and product stakeholders to deliver robust, user-centred solutions.
- Ensure software quality through code reviews, testing, maintainable practices, and long-term system reliability.
- Present research findings through publications, technical documents, conferences, and industry forums.
- PhD, Postdoc, or equivalent industry experience in molecular AI, computational chemistry, or related fields.
- Strong Python and scientific computing skills, including experience with deep learning frameworks for molecular modelling.
- Hands‐on experience with molecular docking, scoring, and molecular dynamics simulations.
- Experience productionising research code into scalable, robust, and maintainable systems.
- Proven ability to collaborate in interdisciplinary teams and communicate complex technical concepts to technical and non‐technical audiences.
- Understanding of data structures, algorithms, and system design principles relevant to scientific software.
- Publications in peer‐reviewed journals related to molecular AI, structure prediction, or computational drug discovery.
- Experience deploying machine learning models into production environments.
- Contributions to open‐source scientific software (e.g., RDKit, OpenMM, PyTorch, or related tools).
Career development and professional growth opportunities. Collaborative culture with a focus on scientific impact and innovation. Exposure to cutting‐edge molecular AI tools and workflows. Opportunity to work on high‐impact drug discovery programmes with real‐world outcomes.
AI Research Engineer (Molecular AI) in London employer: Aspire Life Sciences Search
As a fast-growing life sciences technology organisation, we offer AI Research Engineers the chance to work at the forefront of drug discovery, where your contributions will directly influence real-world health outcomes. Our collaborative culture fosters scientific rigour and innovation, providing ample opportunities for professional growth while you engage with cutting-edge molecular AI tools. Join us in a dynamic environment that values ownership and teamwork, ensuring that your work not only accelerates project timelines but also makes a meaningful impact on global health challenges.
Contact Details:
Aspire Life Sciences Search Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land AI Research Engineer (Molecular AI) in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the AI and life sciences fields on platforms like LinkedIn. Join relevant groups, attend webinars, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to molecular AI or drug discovery. Whether it’s GitHub repos or a personal website, having tangible examples of your work can really set you apart from the competition.
✨Tip Number 3
Prepare for those interviews! Research the company and its projects thoroughly. Be ready to discuss how your experience aligns with their goals, especially in areas like deep learning and molecular modelling. Practice common interview questions and think about how you can demonstrate your problem-solving skills.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of exciting opportunities that might just be the perfect fit for you. Plus, applying directly can sometimes give you an edge over other candidates. So, get your application in and let’s make some waves in the world of drug discovery together!
We think you need these skills to ace AI Research Engineer (Molecular AI) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AI Research Engineer role. Highlight your experience with molecular AI, deep learning, and any relevant projects you've worked on. We want to see how your skills align with our mission in drug discovery!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for AI and drug discovery, and explain why you’re excited about this role at StudySmarter. Let us know how you can contribute to our collaborative culture and scientific impact.
Showcase Your Projects:If you've got any projects or publications related to molecular AI or computational chemistry, make sure to include them! We love seeing real-world applications of your work, so don’t hold back on sharing your achievements.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us. Good luck!
How to prepare for a job interview at Aspire Life Sciences Search
✨Know Your Molecular AI Inside Out
Make sure you brush up on your knowledge of molecular AI and computational chemistry. Be ready to discuss your previous projects, especially those involving deep learning frameworks and molecular modelling. This will show that you’re not just familiar with the concepts but have practical experience too.
✨Showcase Your Collaboration Skills
Since this role involves working closely with engineers and scientists, be prepared to share examples of how you've successfully collaborated in interdisciplinary teams. Highlight any experiences where you translated complex technical concepts for non-technical audiences, as this is key in a collaborative environment.
✨Demonstrate Your Problem-Solving Approach
Think about challenges you've faced in previous roles, particularly in productionising research code or integrating algorithms into software. Be ready to discuss your problem-solving strategies and how you ensure software quality through testing and maintainable practices.
✨Prepare Questions That Matter
Have insightful questions ready for your interviewers. Ask about their current projects, the technologies they use, or how they measure the impact of their AI solutions on drug discovery. This shows your genuine interest in the role and helps you assess if the company aligns with your career goals.
