1 month ago
Responsibilities
- Design end-to-end scientific software architectures spanning data, models, and user-facing applications.
- Apply statistics, optimization, machine learning, and related expertise to solve client R&D problems.
- 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 into scoped tasks and providing domain context and constraints.
- Build data-driven models, AI-based decision-support tools, automated analysis pipelines, and web-based solutions with GUIs and 2D and 3D graphics.
- Design AI-enabled and agentic capabilities into client solutions while balancing speed, reliability, and reproducibility.
- Collaborate with clients to 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 approved, secure AI configurations.
Requirements
- Deep scientific expertise and the ability to translate client R&D problems into working software solutions.
- Knowledge of statistics, optimization, machine learning, and related scientific or engineering fields.
- Ability to direct AI coding agents and evaluate their outputs for correctness and defensibility.
- Ability to solve complex research and product-development problems in collaboration with clients.
- Ability to build models, analysis pipelines, AI-enabled tools, and web-based applications.
- Ability to exercise judgment regarding appropriate uses of AI and generative approaches.
- Strong ownership, analytical ability, curiosity, communication, empathy, integrity, and endurance.
Benefits
- Meaningful work advancing scientific breakthroughs in areas such as drug discovery and sustainable materials.
- Opportunity to work with agentic AI at an automation-first company.
- Collaboration with scientists and engineers across Austin, Cambridge, and Tokyo offices.
- Access to Enthought training programs in Python, machine learning, and scientific computing.
- Flexible hybrid work based out of the Austin office.
- Competitive compensation and benefits.
Tech Stack
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