Staff Technical Program Manager - AI Resources

Job description

Job responsibilities

• Organize, sequence, and prioritize work across our training clusters, data processing pipelines, data operations teams, and other engineering groups so the organization operates at maximum efficiency.
• Allocate our substantial GPU resources across many concurrent model-training projects; work directly with teams to queue critical work, prioritize competing requests, and ensure teams maximize their output.
• Oversee critical data processing pipelines that convert real-world robot experience into the data used to train and control AI models.
• Manage relationships with external vendors who support data annotation and QA at scale.
• Drive consistency, improvement, and efficiency by proactively scheduling resource utilization ahead of critical business events and deadlines.
• Collaborate with AI engineering leadership to define resourcing objectives and priorities, and develop plans and roadmaps that keep infrastructure aligned with the broader AI robotics strategy.
• Identify potential risks to compute or data availability that may impact program delivery; develop mitigation strategies and contingency plans to minimize disruption.
• Engage with key stakeholders, including AI engineers, data operations leads, and executives, to provide updates on resource utilization, gather feedback, and address bottlenecks.

Job requirements

• BS or higher in Engineering or a Technical Related Field (Computer Science, Electrical Engineering, Mechanical Engineering, Physics, etc.) or equivalent work experience.
• Minimum 2 years of experience in a program management role, managing multiple programs and schedules, ideally involving compute or infrastructure resourcing.
• Passion for problem solving and a drive to ask questions and understand the big picture while still being attentive to technical details.
• Strong communication skills and the ability to distill complex technical information into concise, easily understood formats: presentations, white papers, and status updates.
• Proven capacity to leverage an array of project management tools, methodologies, and techniques throughout the AI/ML development lifecycle, including Google Suite, JIRA/Atlassian Products, and similar systems.
• Ability to see, understand, and articulate team priorities in support of overall company and AI strategy goals.
• Experience coordinating across engineering and data teams to manage shared, constrained resources (e.g., GPU/compute clusters, data pipelines).
• Proven experience building sustainable processes within cross-functional groups.