Senior AI​/ML Software Engineer

The Senior R&D Engineer is responsible for the development of materials data products and supporting systems. In this role, the Senior R&D Engineer will focus on developing ML and simulation solutions for materials data problems. Additionally, they will use expertise to support development of strategic plans, refine requirements and provide technical leadership in achieving development objectives in the machine learning and AI domain.

• Develop ML and simulation methods applied to materials data.
• Application of ML methods to products and processes, including identification, evaluation, implementation and maintenance.
• Research the latest ML methods and identify promising areas of research.
• Disseminate ML knowledge and awareness throughout the Materials Business Unit.
• May participate in researching and understanding the marketing requirements for a product. May work with strategic customers or proxies to assess needs and develop solutions.
• Works independently with minimal supervision and may take on some planning and mentoring responsibilities.
• May be responsible for managing interns or co-ops but typically does not have direct reports.

• Expert knowledge of ML models and knowledge of other AI methods such as Large Language Models (LLM) and Generative AI is beneficial.
• Experience of delivering practical solutions by training supervised ML algorithms for solving problems, ideally with materials data.
• BS or MSc in material science, an engineering discipline, or a related physical science subject with 5 years’ experience, or PhD with 1 year experience.

• Technical knowledge with scientific data, backed up with some form of experience with data analysis, and visualization.
• Computational materials modeling experience advantageous.
• Experience leading projects and delivering high-quality technical solutions.
• Ability to overcome obstacles and drive projects to completion.
• Good communication skills in written and spoken English and good interpersonal skills.
• Ability to learn quickly and to collaborate with others in a geographically distributed team.