The role involves building and operating scalable machine learning and data systems alongside simulation workflows and insight tools. The individual will provide technical leadership on large-scale model architectures and oversee the production and optimization of machine learning models. Responsibilities include designing and scaling distributed systems that support dataset generation, model training, and evaluation. The position requires working at the intersection of data engineering, model development, and simulation to improve evaluation processes. Additionally, the role involves collaborating cross-functionally to translate business goals into technical deliverables.

Candidates must possess an M.S. or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related field, or equivalent practical experience. A minimum of 7 years of professional software engineering experience is required, including at least 3 years specifically in machine learning infrastructure. Applicants need a history of contributions to machine learning tooling and frameworks, along with expertise in distributed training techniques and large-scale model architectures. Strong leadership skills and the ability to navigate cross-functional teams are essential for this position.