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RIVR, part of Amazon is a robotics team pioneering Physical AI through real-world deployment and doorstep deliveries. 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 by gathering rich operational data at scale. Key job responsibilities

  • Design and implement a production-grade Linux distribution from scratch using Yocto/OpenEmbedded.
  • Develop and maintain custom Yocto layers, write and patch bitbake recipes, and configure Linux kernels to support specific hardware peripherals.
  • Hardware enablement for critical robotics sensors, including GMSL cameras, GPS/GNSS modules, IMUs, and LiDAR.
  • Implement and manage robust Over-the-Air (OTA) update solutions to ensure safe and atomic fleet-wide deployments.
  • Work closely with hardware engineers to bring up new boards, modify Device Trees, and debug low-level interfaces (I2C, SPI, CAN, UART).
  • Profile and optimize the system for boot time, memory footprint, and interrupt latency. - 4+ years of experience formally leading engineering teams, managing sprints, and coaching developers. - 7+ years of professional experience building and operating large-scale backend systems in a Service-Oriented Architecture (SOA) or microservices context. - Proven experience architecting solutions on AWS. - Proven experience operating a complex SOA architecture at scale. Deep familiarity with failure modes in distributed systems and mechanisms to reduce the blast radius of outages and regressions. - Experience with building and operating ML training infrastructure, integrating it in the SDLC. Experience with handling sensitive data and ensuring its safety and compliance. - Proven ability to delegate and grow, yet remain connected to the technology details. - Strong judgement: you identify and call-out one-way doors, you can independently check Senior Engineers’ assumptions and designs, you anticipate the impact and future cost of shortcuts and weight them against your immediate priorities. - A deep sense of Ownership, a relentless drive to Earn Trust, and a passion for Developing the Best talent. - Exceptional communication skills, with the ability to articulate complex technical ideas clearly to both technical teams and non-technical stakeholders. - Exposure to cloud services communicating with physical edge devices such as robots. - Background in robotics, IoT, fleet management, or real-time data streaming systems. - Familiarity with observability tools (OTLP, Grafana, Prometheus) optimized for physical devices experiencing intermittent connectivity. - Experience with Security topics in the context of cloud systems. - Experience navigating organizational growth or integrating startup systems into large enterprise environments. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( https://www.amazon.jobs/en/privacy_page ) to know more about how we collect, use and transfer the personal data of our candidates. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Prérequis

  • 4+ years of experience formally leading engineering teams
  • 7+ years of professional experience building and operating large-scale backend systems
  • Proven experience architecting solutions on AWS
  • Experience with building and operating ML training infrastructure
  • Exceptional communication skills

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