Principal Engineer, Data Center Hardware Robotics
Sunnyvale, CA, USA · Principal
Sponsorship not specified$275k-$383kDetected 15 hours ago
GCPFPGAEmbedded SystemsSystems EngineeringRoboticsSensorsControlsResearchLeadership
About the role
- About the job The AI and Infrastructure (AI2) team is redefining what's possible.
Responsibilities
- Collaborate closely with executive leadership, internal and external, regarding AI2's data Center Robotics strategy and ecosystem development.
- Lead engineering execution and provide technical leadership for product features and delivery.
Requirements
- PhD degree in Robotics or a related technical field, or equivalent practical experience.
- 15 years of experience in robotics systems engineering or architecture, and experience with technical innovation.
- Experience in the robotics industry, leading robotics applications development and turning Research and Development (R&D) into deployed, real world systems.
- Experience in robotic control, planning, kinematics, and mechatronic systems.
Nice to have
- Experience with embedded systems (e.g., RTOS, microcontrollers, FPGA), sensor fusion, and actuator control.
- Familiarity with motion control systems and robotics programming languages (e.g. Robot Operating System) or similar frameworks.
- The AI and Infrastructure (AI2) team is redefining what's possible.
- As Principal Engineer, you will define the strategic and technical direction for PIE Robotics roadmap.
- The AI and Infrastructure team is redefining what's possible.
- Scope and develop advanced robotics automation technical solutions for data center hardware required for AI2 business transformation.
- Source and ensure AI2 captures the latest Robotics and AI technologies and solutions from the ecosystem, and rapidly deploy within AI2, to meet the business needs.
- Oversee the end-to-end deployment of autonomous mobile robots (AMRs), automated guided vehicles (AGVs), and multi-axis robotic arms for handling delicate data center hardware.
Compensation
- $275k-$383k
This listing is sourced directly from Google's careers page and normalized into a canonical job model.