1 month ago
Cambridge, United KingdomSenior
Responsibilities
- Design end-to-end scientific solutions that translate client R&D problems into architectures spanning data, models, and user-facing applications.
- Use AI coding assistants and autonomous coding agents to explore data, prototype models, build software, write tests, and create documentation.
- Direct AI agents by decomposing scientific and engineering problems, providing domain context and constraints, and iterating toward defensible results.
- Build data-driven models, AI-based decision-support tools, automated analysis pipelines, and web-based solutions with GUIs, 2D/3D graphics, and cloud computing.
- Collaborate directly with client researchers and business leaders to solve research and product-development problems and define, demonstrate, and refine solutions.
- Participate in code reviews, architecture reviews, sprint planning, retrospectives, and daily standups.
- Handle client data and intellectual property responsibly using AI tools only in approved, secure configurations.
Requirements
- Deep scientific expertise and the ability to apply statistics, optimization, machine learning, and related disciplines to client R&D problems.
- Ability to build software, models, analysis pipelines, and AI-enabled decision-support tools for scientific and engineering applications.
- Ability to direct AI coding agents and evaluate when generative approaches are appropriate while maintaining reliability and reproducibility.
- Ability to collaborate closely with clients, researchers, business leaders, scientists, and engineers.
- Strong integrity, analytical ability, ownership, communication, curiosity, and ability to simplify complex problems.
Benefits
- Meaningful work supporting scientific advances such as drug discovery and sustainable materials.
- Opportunity to work at an automation-first company focused on agentic AI.
- 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
Solutions Engineering
