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-centered 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).

Benefits

• Hybrid working model (UK).
• 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.

Your consultant

As a Recruitment Consultant at Aspire Life Sciences, Jack Wilson specialises at the intersection of technology and life sciences. He focuses on placing high-level Data, AI and Machine Learning talent with fast-growing startups across the UK, Europe, and the USA. Jack’s deep industry insight allows him to connect candidates with roles where cutting-edge technology meets life-saving healthcare innovation.