Technical Program Manager – AI/ML

Position Overview

We’re hiring a Technical Program Manager - AI/ML to drive cross-functional execution across research, engineering, and operations as we scale embodied AI systems for robotics. You’ll translate frontier AI research into production-ready systems, building the structure, alignment, and momentum needed to move from prototype to real-world deployment.

This is a high-impact role at the center of our technical organization, shaping how foundational AI models become robust, scalable robotic intelligence.

Responsibilities

• Own end-to-end program execution for AI/ML initiatives, from model development and experimentation through deployment into robotic systems.
• Partner closely with research, ML engineering, robotics, data, and infrastructure teams to align roadmaps and deliver integrated systems.
• Translate ambiguous, research-heavy objectives into structured execution plans with clear milestones and measurable outcomes.
• Drive cross-functional AI programs spanning data generation, model training, evaluation frameworks, simulation, and real-world validation.
• Establish and track program-level KPIs such as model performance, data efficiency, training velocity, system reliability, and deployment readiness.
• Identify execution risks early (technical, operational, resourcing) and proactively mitigate them.
• Build scalable processes for managing experimentation cycles, compute planning, and large-scale model iteration.
• Facilitate executive reviews and ensure leadership has clear visibility into progress, trade-offs, and strategic decisions.
• Continuously improve program management frameworks to support rapid research velocity while maintaining engineering rigor.

Preferred Qualifications

• 5+ years of experience in a fast-paced startup-like environment.
• 2+ years in a technical role (Engineer, Technical Program Manager, Product Manager, or similar) at a technology company.
• Strong technical fluency in AI/ML systems (e.g., model training workflows, data pipelines, evaluation systems, infrastructure constraints).
• Demonstrated ability to manage complex, ambiguous, research-driven programs.
• Proven track record of driving cross-functional collaboration across engineering, research, and operations teams.
• Strong technical problem-solving skills with the ability to quickly understand complex ML and robotics systems.
• Experience defining and tracking metrics for technical systems.
• Proven ability to communicate effectively with senior leadership and influence decision-making.