Robotics Systems Engineer

Skild AI•San Mateo, CA
•$175,000 - $275,000

About The Position

Skild AI is developing general-purpose robotic intelligence that adapts to unseen scenarios, using large-scale data-driven machine learning to support widespread robot deployment. The company is seeking a Robotics Systems Engineer to own the system-level architecture, integration, and reliability of a new robotic platform. The role spans mechanical design, electrical integration, embedded firmware, and ML policy deployment, and will contribute to product architecture decisions and demonstrate platform readiness through testing against external standards and internal targets.

Requirements

  • At least 5 years of experience in systems engineering, mechatronics, or robotics hardware development.
  • Strong fluency across mechanical assemblies, custom wire harnessing, power electronics, sensor integration, and embedded communication protocols.
  • Proficiency with Linux-based robotics tools such as ROS/ROS2 and system telemetry, bench debugging equipment such as multimeters, oscilloscopes, and logic analyzers, and test scripting in Python or C++.
  • Experience taking complex electromechanical or robotic products from early prototyping through verification and high-reliability field deployment.
  • Ability to work in a fast-paced startup environment with ambiguous requirements and tight iteration loops.

Nice To Haves

  • Experience deploying ML policies or AI-driven control loops directly onto physical hardware.
  • Hands-on experience with industrial functional safety standards such as ISO 13849 or IEC 61508, or with EMI/EMC compliance for mobility platforms.
  • Background with high-performance BLDC actuators, cycloidal or harmonic drive gearboxes, and high-density battery management systems.

Responsibilities

  • Define system-level specifications, interfaces, power budgets, and sensor suites across quadrupeds, humanoids, and custom mobility platforms.
  • Lead hands-on bring-up of sensors, compute payloads, actuation systems, and custom power distribution architectures on third-party and in-house robotic hardware.
  • Build hardware qualification pipelines, end-of-line functional tests, and diagnostic frameworks to verify system readiness before field deployment.
  • Perform FMEA and conduct root-cause investigations into hardware failures from field operation or policy stress testing.
  • Partner with ML research engineers, mechanical design teams, and manufacturing technicians to translate software performance goals into hardware requirements and physical test fixtures.
  • Standardize sensor synchronization protocols, communication topologies, and cabling architectures for hardware survivability in high-impact industrial operations.
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