Feeny
Skild AI

Senior Robot Infrastructure Engineer at Skild AI (San Francisco, CA)

Skild AI· San Francisco, CA· $100k–$300k·

Role details

Salary
$100k–$300k

Job description

Company Overview

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.

Position Overview

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.

Responsibilities

  • Design, implement, and maintain production-grade C++ and Go running directly on robotic platforms.
  • Build on-device systems for interfacing with core robotics software, managing local data buffering, and handling edge-side communication logic.
  • Architect and maintain secure, low-latency edge-to-cloud data pipelines connecting deployed robot fleets to cloud infrastructure and web platforms.
  • Design, build, and operate OTA update mechanisms for safely and reliably deploying software updates to robots in the field.
  • Build telemetry, alerting, logging, and monitoring tools across the robot operating system, cloud infrastructure, and fleet dashboards.
  • Optimize edge software for reliability, performance, resource usage, and resilience under real-world deployment constraints.
  • Collaborate with autonomy, hardware, deployment, and web product teams to support new features powered by live robot data and fleet-scale infrastructure.
  • Continuously improve fleet reliability, observability, uptime across both device and cloud systems.

Preferred Qualifications

  • 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

Base Salary Range $100,000—$300,000 USD

Why work at Skild AI

  • Innovation‑driven culture: Described as a team where “curiosity meets impact,” tackling the frontier of physical AI.
  • Diverse openings: 50+ roles across engineering (CV/ML, manipulation, embedded, simulation, infrastructure), research, product, operations, and marketing.
  • Global presence: Offices in Pittsburgh, San Mateo, San Francisco (US) and Bengaluru (India); some roles allow remote work, though many are location‑specific.
  • Engineering‑forward: Emphasis on data‑driven machine learning, robotics, and large‑scale systems, with opportunities to work on the core AI model and deployment.
  • Perks: Not detailed, but typical for venture‑backed robotics startups include competitive equity, modern hardware, and a mission‑oriented environment.

Application questions