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The Data Engineer will build data pipelines for materials science, ensuring data quality and collaborating with ML researchers while managing large datasets.

You will lead the development of internal applications for material discovery, ensuring they are high-quality products through collaboration and iterative design.

Develop intelligent agents for a materials discovery engine, orchestrating scientific workflows and integrating experimental design for sustainability solutions.

Own and scale People Operations: build and document end-to-end people processes, administer HRIS (e.g., Deel) and people data, ensure multi-jurisdictional compliance, support payroll/benefits and immigration, drive cross-functional projects, automate workflows, and serve as primary employee contact to maintain a reliable operational backbone during rapid growth.

Lead full-cycle recruiting for Technical Partnerships and Business Development roles at a deep-tech AI company. Build sourcing strategies, partner with hiring teams on assessments and calibration, manage offers and onboarding, maintain ATS data hygiene, advise on market compensation and DEIB, and deliver an exceptional candidate experience to scale the partnerships and research talent pipeline.

As an ML Research Engineer, you will develop computational methods and infrastructure to enhance molecular simulations and machine learning force fields for materials discovery.