Head of QA

RIVR is a Swiss robotics company pioneering Physical AI and robotic solutions to revolutionize last-mile delivery, giving 1 human the power of 1000. Through the combination of artificial neural networks and innovative robot designs with wheels and legs, RIVR aims to enhance efficiency, sustainability, and scalability in last-mile delivery. Founded as Swiss-Mile, the company rebranded to RIVR in 2025 to better reflect its mission of driving the future of intelligent robotics. Join our innovative team, renowned for pioneering robotic design and neural network applications in robotics that improve environmental understanding and decision-making. With a robust research foundation and notable contributions from ETH Zurich, we are leaders in translating artificial intelligence and robotics into practical, real-world applications.
RIVR is committed to building a diverse and inclusive team that values every perspective. If you’re passionate about driving innovation in robotics and creating meaningful impact, we encourage you to apply and bring your unique self to our team.
Job Description
We are looking for a Head of QA to build and lead RIVR’s end-to-end Quality Assurance organization across the full System, Autonomy, Hardware, and Operations. 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.

What you’ll be doing

Build and lead RIVR’s end-to-end QA organization across the full System, Autonomy, Hardware, and Operations.

Define and implement a scalable quality strategy for robotics fleets inspired by autonomous vehicles and robotics best practices.

Establish validation workflows that gate all hardware and software releases before fleet deployment.

Partner closely with Software and Hardware Engineering to embed quality early in the development lifecycle.

Develop automated testing frameworks across Software-in-the-Loop (SiL), Hardware-in-the-Loop (HiL), and real-world testing.

Define quality KPIs, release criteria, and reliability targets at robot and fleet scale.

Build regression, performance, and safety validation pipelines for autonomy and AI systems.

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 rapid product iterations and growing deployments.

What you must have

Leadership experience.

Proven experience leading QA (10+ years) 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.

Experience defining release gates, quality KPIs, and reliability targets for deployed fleets.

Strong systems engineering mindset with the ability to operate across autonomy, hardware, and operations.

Hands-on experience with automation frameworks, test infrastructure, and regression pipelines.

Ability to work cross-functionally with Software, Hardware, and Product teams in fast iteration cycles.

Experience with safety, compliance, and field reliability feedback loops.

Strong leadership skills with a track record of building and scaling high-performing teams.

Comfortable operating in high-growth startup environments with evolving processes and products.

Get some bonus points

Experience in autonomous driving, mobile robotics, or last-mile delivery robots.

Familiarity with safety standards.

Experience validating AI/ML or Vision-Language-Action (VLA) autonomy systems.

Background in simulation environments and large-scale scenario testing.

Exposure to fleet operations, teleoperation, and remote supervision systems.

Experience with reliability engineering, HALT/HASS, and environmental testing.

Knowledge of regulatory certification processes for robots operating in public spaces.

Experience scaling QA organizations from prototype to mass deployment.

Familiarity with DevOps/MLOps pipelines and continuous integration for robotics.

Hands-on robotics or mechatronics background.