Staff Technical Program Manager - AI Resources

Boston Dynamics•Waltham, MA

1d•$130,000 - $150,000

About The Position

As a Technical Program Manager within Boston Dynamics PMO, you will be an integral part of the core program leadership, accountable for the operational efficiency of the resources that power our AI teams. You will own the sequencing and prioritization of work across our training clusters, data processing pipelines, and data operations teams, ensuring our engineers can move as fast as possible as we scale our AI robotics strategy. The ideal candidate will have considerable influence over how AI infrastructure resources are allocated and will regularly engage with AI engineering leads and stakeholders to ensure successful outcomes. We're seeking a self-motivated individual capable of balancing strategic vision with meticulous attention to detail, essential for fostering consensus amidst competing demands for limited compute. A crucial skill you'll possess is the ability to discern dependencies across engineering, data, and infrastructure teams, adeptly navigating complex tradeoffs, and integrating them into a cohesive resourcing plan. Boston Dynamics is a world leader in mobile robots, tackling some of the toughest robotics challenges. For years, our awe-inspiring viral videos on YouTube have shown the world what remarkably capable robots can do. Now we are quickly becoming a recognized leader in automation solutions for industrial applications and warehouse logistics.

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.
Excellent leadership and interpersonal skills; ability to effectively collaborate with diverse teams and stakeholders, both technical and non-technical.

Nice To Haves

Direct experience managing GPU or training cluster resource allocation.
Familiarity with data annotation/QA vendor management for ML pipelines.
Broad technical background and understanding of AI/ML model training workflows, ideally in a robotics context.

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.
Drive process improvements and best practices for resource allocation and utilization tracking; conduct post-program reviews to identify areas for improvement.
Drive other program deliverables across AI infrastructure and the teams dedicated to building BD's internal AI tools and capabilities.
Manage data procurement and contract negotiations.
Investigate and source commercial training data sets needed for future modeling.