Tech Lead Testing, Amazon Robotics

RIVR, an Amazon company, is building Physical AI by deploying autonomous robots for real-world doorstep delivery. Operating daily in diverse urban environments, RIVR's robots continuously learn from and navigate the millions of scenarios encountered during deliveries. By owning the full stack from software to hardware, RIVR is purpose-built for safety, reliability, and the customer from day one.

This is a hands-on leadership role. You will still design test benches, write automation code, and dig into data, but you will also mentor engineers, drive process maturity, and represent testing in cross-functional planning. If you combine deep technical expertise in hardware testing with the ability to set priorities, grow people, and influence design outcomes, this role offers a unique opportunity to shape how a Physical AI company validates its products.

Key job responsibilities

Technical Leadership & Strategy

Define and own the end-to-end test strategy for structural, mechatronic, and sensing subsystems, aligned with product development milestones.

Establish testing standards, processes, and best practices across the team, including test plan templates, data management workflows, and reporting formats.

Make architectural decisions on test infrastructure: investments into instrumentation platforms, automation frameworks, and data pipelines.

Drive continuous improvement of test coverage, efficiency, and predictive capability.

Hands-On Testing & Engineering

Design, commission, and operate test benches for mechatronics systems (actuators, mechanism, cabling and sensor), including fixture design, instrumentation layout, and safety concepts.

Select, integrate, and calibrate sensors, load cells, thermocouples with a thorough understanding of their working principles and error influences.

Develop and maintain automation scripts (Python, Labview) to control test hardware, execute stress and performance tests, and log critical data.

Process and analyze test data applying signal processing and statistics fundamental to extract meaningful performance metrics.

Reporting & Design Influence

Compile clear, structured test reports that compare results against specifications, highlight anomalies, and derive actionable engineering learnings to feed back into the design cycle.

Identify failure modes, performance bottlenecks, and reliability risks, translating findings into concrete design recommendations.

Represent the test function in design reviews, providing data-driven input on FMEA, and qualification criteria.

Team & Collaboration

Mentor and grow test engineers, fostering technical depth and a culture of rigorous, curiosity-driven experimentation.

Collaborate closely with mechanical, electrical, firmware, and systems engineers to align test strategies with product requirements.

Coordinate with external test labs and suppliers when specialized testing is required.

Basic qualifications

- 7+ years of experience in hardware testing or validation, with at least 3 years in a technical leadership or senior individual contributor role.

- Proven experience designing and commissioning test benches for electro-mechanical system or consumer electronics with significant power and motion elements.

- Strong scripting proficiency in Python for test automation, device control, and data analysis.

- Practical knowledge of sensors and instrumentation - torque cells, encoders, load cells, thermocouples, strain gauges, including their working principles, error influences, and calibration requirements.

- Demonstrated ability to turn test data into clear engineering insights that influence design decisions.

- Experience developing and reviewing test plans, test cases, and qualification criteria.

- The ability to work hands-on in a workshop environment and use common tools safely.

- Master's degree in Mechanical Engineering, Electrical Engineering, Mechatronics, Robotics, or a related technical field.

Preferred qualifications

- Experience with motor or actuator characterization (efficiency mapping, cogging-torque analysis, thermal correlation).

- Familiarity with test automation frameworks (LabVIEW, pytest) or hardware-in-the-loop setups.

- Understanding of measurement uncertainty analysis (GUM) and calibration procedures.

- Hands-on experience with ROS/ROS2.

- Experience with CAD software (SolidWorks, Fusion 360, or similar) for designing test fixtures.

- Knowledge of data acquisition (DAQ) hardware and system integration.

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