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Salary: USD 142,200 - 193,000 / annual
Niantic Spatial is building physical AI technology powered by a proprietary database of over 30 billion posed images. The company's mapping and Visual Positioning System technology serves robotics, public sector, and energy/industrial markets.
The Real-World Test Lab (RWTL) is a new team that bridges the gap between benchmarks and real-world deployment. As Niantic Spatial's first and most demanding customer, the Lab tests reconstruction, localization, and spatial understanding under authentic field conditions—factory floors, substations without GPS, challenging lighting—to validate what gets built next.
You will own the physical layer of evidence generation as a Hardware Operations Engineer reporting to the Director of the Real-World Test Lab. Your core responsibilities include:
**Fleet & Characterization**: Manage the complete lifecycle of capture devices, sensors, and robots—inventory, calibration, firmware, maintenance, logistics, and spares. Document each platform's capabilities and limits so hardware constraints are known quantities, not surprises in results.
**Physical Test Environments**: Design and operate controlled test spaces across the office, rented facilities, and partner/customer sites. Engineer layout, lighting, markers, obstacles, and survey-grade ground truth references so environment becomes a controlled variable.
**Instrumentation & Measurement**: Build rigs, mounts, references, and measurement setups that convert physical runs into quantitative data: trajectory ground truth, positional accuracy, sensor synchronization, and automated condition logging.
**Evaluation System Integration**: Work with the AI Automation Engineer to feed physical results into the same automated scorecards and comparisons as software evaluations, replacing spreadsheets and file folders with structured metadata and data offload.
**Test Execution**: Run robot bring-up, teleoperation, scripted trials, and repetitive sessions that produce statistically meaningful results rather than anecdotes.
**Sim-to-Real Validation**: Engineer and execute the physical counterpart to simulation scenarios, matching environment, route, lighting, sensor config, and robot setup, with instrumentation that explains divergence.
**Safety Ownership**: Define and maintain safe operating procedures for robots and powered equipment; coordinate with workplace services, IT, Legal, and site owners.
**Automation**: Script configuration, calibration checks, data offload, and condition logging so colleagues can run sessions independently.
**Success Milestones**: By 30 days, complete fleet inventory/characterization and define safe operating procedures. By 60 days, execute first instrumented robot run with repeatable documentation in the evaluation system. By 90 days, operate test environments with controlled conditions, support data acquisition smoothly, and run standing sim-to-real protocols.
**Requirements**
- Hands-on engineering experience with robotic hardware: bring-up, integration, teleoperation, troubleshooting, maintenance (mobile/wheeled platforms preferred)
- Built test rigs, fixtures, or instrumentation producing quantitative measurements of physical systems
- Designed and run structured physical experiments with rigorous ground truth methodology and reproducible documentation
- Experience with sensor calibration, multi-sensor synchronization, coordinate frame conventions, and error propagation analysis
- Strong Python and command-line proficiency; track record automating hardware configuration, data offload, or test execution
- Operational hardware fleet management: inventory, firmware, calibration schedules, logistics, repair coordination
- Practical safety experience operating powered equipment or robots around people
- Bachelor's degree in relevant field or equivalent experience
**Nice to Have**
- ROS or ROS 2 experience (writing nodes, integrating sensor drivers)
- NVIDIA Isaac Sim or Isaac Lab user experience
- Professional capture hardware (terrestrial laser scanners, NavVis, Leica, LiDAR, 360 cameras, drones)
- Survey-grade or motion-capture ground truth for localization/navigation evaluation
- Photogrammetry, Gaussian splat, or 3D reconstruction capture support
- Test operations at customer/partner sites
