The role involves leading the development of advanced AI and machine learning infrastructure for multi-billion parameter foundation models within simulation environments. The engineer will design and scale large distributed systems that support planet-scale dataset generation and model training. Responsibilities include providing technical leadership on large-scale model architectures and working at the intersection of data engineering, model development, and deployment. The position requires collaborating with cross-functional teams to derive system-level requirements and translate business goals into technical deliverables. Additionally, the role involves mentoring junior engineers to foster a collaborative team culture.

The role requires a Bachelor of Science in Computer Science, Robotics, or a similar technical field, or equivalent practical experience. Candidates must possess at least five years of professional software engineering experience, including a minimum of three years specifically in machine learning infrastructure. Preferred qualifications include a Master of Science in a relevant technical field and ten or more years of professional software engineering experience. Expertise in distributed training, model scaling, and machine learning infrastructure tools is necessary for this position.