1 month ago
Cambridge, United KingdomSenior
Responsibilities
- Design end-to-end materials informatics architectures covering data, models, and user-facing applications.
- Build data-driven models, AI-based decision-support tools, automated analysis pipelines, and web-based solutions with GUIs, 2D/3D graphics, and cloud computing.
- Use and direct AI coding assistants and autonomous coding agents for data exploration, prototyping, software development, testing, and documentation.
- Translate materials and chemistry research problems into well-scoped technical tasks and guide agents toward correct, defensible results.
- Collaborate directly with client researchers and business leaders to define, demonstrate, and refine solutions.
- Evaluate where AI and generative methods are appropriate for small, sparse, and noisy materials R&D datasets.
- Participate in code reviews, architecture reviews, sprint planning, retrospectives, and daily standups.
- Handle client data and intellectual property responsibly using approved, secure AI-tool configurations.
Requirements
- Deep expertise in materials science and chemistry.
- Experience applying machine learning to materials or chemistry problems.
- Ability to design architectures spanning data, models, and user-facing applications.
- Ability to build scientific software, analysis pipelines, AI-based tools, and web-based solutions.
- Ability to collaborate with client researchers and business leaders and communicate complex technical problems clearly.
- Ability to direct AI agents by providing domain context and physical constraints.
- Sound judgment regarding the use of AI and generative approaches with small, sparse, and noisy datasets.
- Strong ownership, analytical ability, curiosity, integrity, communication, empathy, and endurance.
Benefits
- Meaningful work advancing drug discovery and sustainable materials development.
- Opportunity to work with agentic AI and help shape automation-first scientific workflows.
- Collaborative colleagues and a global culture across Cambridge, Austin, and Tokyo offices.
- Access to Enthought training programs in Python, machine learning, and scientific computing.
- Flexible hybrid work based out of the Cambridge office.
- Competitive compensation and benefits.
Tech Stack
Categories
ML EngineeringSolutions Engineering
