AI Research Engineer; Molecular AI

This role is for AI research engineers who want to design, build, and product ionise 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.

• Design, develop, and product ionise 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 product ionising 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.

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.