VP of Hardware

Rhoda ai•Palo Alto, CA

About The Position

At Rhoda AI, we're building the full-stack foundation for the next generation of humanoid robots — from high-performance, software-defined hardware to the foundational models and video world models that control it. Our robots are designed to be generalists capable of operating in complex, real-world environments and handling scenarios unseen in training. We work at the intersection of large-scale learning, robotics, and systems, with a research team that includes researchers from Stanford, Berkeley, Harvard, and beyond. We're not building a feature; we're building a new computing platform for physical work — and with over $400M raised, we're investing aggressively in the R&D, hardware development, and manufacturing scale-up to make that a reality. We are looking for a VP of Hardware Engineering to lead the design, development, and scaling of Rhoda's robotic systems from concept through volume production. This is a critical leadership role responsible for building and managing a high-performance hardware organization, defining product architecture, and delivering best-in-class systems that meet the demands of real-world industrial deployment. Robotics has historically been limited by hardware systems that cannot operate reliably in real-world environments at scale. At Rhoda, we are solving that problem.

Requirements

15+ years of experience in hardware/system development, including senior leadership roles
Proven track record of taking complex hardware systems from concept to volume production
Deep experience across the full product lifecycle: requirements definition, system architecture, design & development, test & validation, NPI & manufacturing scale-up
Strong experience with contract manufacturing and global supply chains
Experience leading safety, certification, and compliance efforts
Demonstrated ability to build and lead high-performing engineering teams
Experience working closely with product management and cross-functional teams

Nice To Haves

Experience building and shipping commercially scaled robotic systems
Background in robotics, automation, or industrial systems
Experience with high-reliability systems deployed in real-world environments
Familiarity with hardware/software/AI system integration
Candidates without direct robotics experience are encouraged to apply if they have led the full lifecycle development of complex hardware systems in adjacent industries (e.g., automotive, aerospace, industrial equipment, or consumer electronics).

Responsibilities

Partner with Product Management to define system requirements and product roadmaps
Translate product requirements into clear engineering specifications and system architectures
Drive end-to-end hardware development across mechanical, electrical, and system domains
Lead the design and development of robotic systems including manipulation platforms, end effectors, sensor integration, and compute and control systems
Ensure systems are robust to real-world operating conditions (variability, wear, safety, uptime)
Oversee full product lifecycle: Concept → Prototype → Validation → NPI → Volume Production
Build and manage rigorous test and validation processes (functional, reliability, safety)
Establish engineering processes and standards to support rapid iteration without compromising quality
Lead New Product Introduction (NPI) and transition to volume production
Working together with operations and supply chain teams, develop and manage relationships with contract manufacturers and key suppliers
Drive cost optimization, yield improvement, and supply chain resilience
Oversee safety engineering and certification processes (CE, ISO, etc.)
Ensure systems meet regulatory and industrial deployment requirements globally
Build and lead a world-class hardware engineering team across mechanical, electrical, and systems engineering
Establish a culture of execution, ownership, and first-principles problem solving
Drive bold innovation across the hardware organization — encourage the team to push beyond existing approaches, rapidly iterate, and learn from real-world data