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- Tasks: Design and build AI solutions for drug discovery, impacting real-world health.
- 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.
- 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.
- Other info: Collaborative environment with opportunities for professional growth and innovation.
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.
Skills & expertise
- 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.
Nice to have
- 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) employer: Aspire Life Sciences Search
Contact Detail:
Aspire Life Sciences Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Research Engineer (Molecular AI)
✨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, especially those related to molecular AI or drug discovery. This could include code samples, research papers, or even presentations. Having tangible evidence of your expertise can really set you apart from the competition.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with deep learning frameworks and how you've collaborated with interdisciplinary teams. Practising common interview questions can help you feel more confident when it’s your turn to shine!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, applying directly can sometimes give you an edge, as it shows your enthusiasm for the role and the company.
We think you need these skills to ace AI Research Engineer (Molecular AI)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of AI Research Engineer. Highlight your experience with molecular AI, deep learning frameworks, and any relevant projects that showcase your skills in drug discovery.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're passionate about using AI in drug discovery. Share specific examples of your work and how it aligns with our mission to accelerate drug discovery across various health challenges.
Showcase Your Collaboration Skills: We value collaboration, so be sure to mention any interdisciplinary projects you've worked on. Highlight how you’ve communicated complex concepts to both technical and non-technical audiences.
Apply Through Our Website: For the best chance of success, apply directly through our website. This ensures your application gets to the right people and shows us you're genuinely interested in joining our team!
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 can also apply them practically.
✨Showcase Your Collaboration Skills
Since this role involves working closely with engineers, scientists, and product stakeholders, 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 crucial for effective communication.
✨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 a list of insightful questions ready for your interviewers. Ask about their current projects, the technologies they use, and how they envision the future of molecular AI in drug discovery. This shows your genuine interest in the role and helps you assess if the company culture aligns with your values.