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Zürich, Zürich, Schweiz/Suisse/Svizzera/Svizra
Onsite
RIVR, part of Amazon is a robotics company pioneering Physical AI through real-world doorstep delivery. Founded in 2024 as an ETH Zurich spin-off, RIVR developed wheeled-legged robots designed to operate in complex, unstructured environments such as stairs, gates, doors, and uneven urban terrain. We believe that achieving general physical intelligence requires solving real customer problems in the real world, where robots can learn from rich operational data at scale.
Following our acquisition by Amazon in March 2026, we are continuing this mission with greater reach and speed. By combining custom robot hardware, onboard autonomy, and cloud-based coordination, RIVR, part of Amazon is building the next generation of safe, reliable autonomous robots for last-mile delivery
We are looking for a Head of QA to build our Quality Assurance and Verification department from the ground up. In this role, you will break down existing departmental silos (Hardware, Software, and AI) to establish a unified, company-wide System-level Quality Gate. Inspired by best practices from autonomous vehicles and robotics, this role will establish a scalable quality workflow that validates all hardware and software changes before they reach deployed fleets. Operating in parallel to Software and Hardware Engineering, the Head of QA will work closely with developers to embed quality early in the development lifecycle, balancing rigorous validation with rapid product iteration. Over time, the organization will expand automation capabilities across software-in-the-loop, hardware-in-the-loop, and real-world operational testing to ensure reliability, safety, and performance at fleet scale.
Build and lead Amazon RIVR’s end-to-end QA organization across the full System, Autonomy, Hardware, and Operations from "A to Z".
Define and implement a scalable quality strategy for robotics fleets inspired by autonomous vehicles and robotics best practices.
Establish a unified validation workflow to break down silos and transition from engineer-led testing to a centralized, automated pipeline.
Partner closely with Software and Hardware Engineering to embed quality early in the development lifecycle, acting as a technical partner rather than a corporate gatekeeper.
Architect and scale a Hardware-in-the-Loop (HiL) farm to automate the testing of complex mechatronic variables.
Develop automated testing frameworks across Software-in-the-Loop (SiL), Hardware-in-the-Loop (HiL), and real-world testing.
Take ownership of safety governance and establish high-velocity pipelines (e.g., 14-day fixes) for critical field safety reports.
Define quality KPIs, release criteria, and reliability targets at robot and fleet scale.
Oversee field quality, maintenance feedback loops, and operational performance monitoring.
Drive root-cause analysis and continuous improvement across hardware and software failures.
Scale QA infrastructure, tooling, and team processes to support the target of manufacturing up to two million robots.
Pioneer Leadership experience: 10+ years leading QA or Validation teams with a proven track record of building departments in high-growth environments.
Proven experience leading QA or Validation teams in robotics, autonomous vehicles, automotive, or other safety-critical systems.
Track record of building scalable quality processes for both hardware and software products.
Deep understanding of validation methodologies across SiL, HiL, and real-world testing.
Strong mechatronic and systems engineering mindset with the ability to bridge Hardware, Firmware, and AI/ML Autonomy.
Hands-on mastery of automation frameworks, test infrastructure (e.g., dSPACE), and regression pipelines.
Ability to work cross-functionally with Software, Hardware, and Product teams in fast iteration cycles.
Experience with safety, compliance (e.g., UL2, ISO 26262), and field reliability feedback loops.
Comfortable operating in high-growth startup environments with evolving processes and products
Experience in autonomous driving, mobile robotics, or last-mile delivery robots.
Advanced degree (MSc/PhD) from top-tier engineering institutions.
Experience validating AI/ML or Vision-Language-Action (VLA) autonomy systems.
Background in simulation environments and large-scale scenario testing.
Experience scaling QA organizations from R&D prototypes to high-volume mass deployment.
Knowledge of regulatory certification processes for robots operating in public spaces.
Familiarity with MLOps pipelines and continuous integration for robotics.