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At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.
We are seeking a versatile Robotics Infrastructure Engineer to build the edge-to-cloud systems that connect, manage, update, and monitor our robot fleet at scale. Your work will span on-device software, cloud infrastructure, fleet observability, OTA updates, and reliable connectivity in real-world environments. You should be comfortable writing production-grade C++ and Python on robots while also designing secure, low-latency pipelines into cloud and web platforms. This role involves close collaboration with robotics, autonomy, hardware, deployment, and web product teams to unlock new capabilities powered by real-time robot data.
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3+ years of relevant industry experience.
Strong production programming experience in C++ and Go.
Prior experience deploying, operating, or managing connected hardware, IoT devices, or robotic systems at scale.
Experience architecting and managing cloud infrastructure, including services such as AWS, GCP IoT Core, EC2, S3, Lambda, or related technologies.
Deep understanding of networking protocols commonly used in robotics, IoT, or constrained environments, such as MQTT, WebSockets, gRPC, or similar protocols.
Demonstrated experience building or managing OTA update systems for edge devices or deployed fleets.
Strong systems-level understanding of edge computing constraints, including CPU, memory, storage, power cycles, connectivity loss, and local data persistence.
Experience building fleet observability systems, including telemetry, metrics, logging, alerting, monitoring, and uptime tracking.
Strong focus on reliability, fault tolerance, self-healing infrastructure, and safe operation of deployed systems.
Experience with OS-level OTA infrastructure or full-device update mechanisms
Robotics AI startup building the world's first general-purpose robotic intelligence designed to be robust and adaptable to unseen scenarios through large-scale data-driven machine learning.
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