Develop, deploy, and integrate machine learning and deep learning models for scientific and industrial problems (materials, chemistry, process optimization). Build data pipelines, feature engineering, model evaluation, and scalable production integrations. Collaborate with scientists, engineers, product, and customer teams to translate domain problems into AI solutions, support deployments, and communicate results. Conduct strategic research and stay current with AI/ML methods; periodic customer travel.

Early-to-mid career Product Manager to translate customer needs into product requirements for AI-driven scientific SaaS. Work cross-functionally with engineering, AI/ML, solutions, and commercial teams to prioritize backlog, run discovery, support launches, gather customer feedback, and define product metrics for customers in chemistry, manufacturing, and energy.