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Salary: USD 140,000 - 230,000 / annual
Skild AI is building general-purpose robotic intelligence that adapts to unseen scenarios through data-driven machine learning. We seek an experienced Electrical Engineer to own electrical system integration across our robotics platforms, serving as a key bridge between software/firmware and kinematic motion control.
You will be the internal expert for grounding, shielding, filtering, signal integrity, wireless integration, and EMC from concept through production. This is a hands-on role requiring sound system-level tradeoffs as requirements evolve, balancing electrical performance, mechanical constraints, cost, reliability, manufacturability, and schedule.
Key responsibilities include:
- Develop, test, and validate power and sensor electronics systems
- Design and validate motor driver circuits and power electronics systems
- Integrate and fuse sensor data (IMUs, encoders, hall sensors, temperature sensors) at the PCB level
- Define grounding, bonding, shielding, filtering, and cable strategies across the robot
- Identify EMC risks early and drive practical mitigations before late-stage issues arise
- Debug EMC and hardware issues using scopes, spectrum analyzers, probes, LISNs, network analyzers, and lab equipment
- Make system-level tradeoffs across performance, risk, cost, schedule, and manufacturability
- Partner across EE, ME, firmware, controls, systems, manufacturing, and external labs
- Document design processes and contribute to hardware best practices
Ideal candidates have a Bachelor's or Master's in Electrical Engineering, Robotics, Mechatronics, or related field, plus hands-on experience taking electrical hardware from concept through validation and production. Strong expertise in EMC/EMI design, power electronics, motor drives, sensor integration, RF systems, PCB design, and communication protocols (GMSL, CAN, Ethernet, USB, SPI, I2C, RS-485) is essential. You should be comfortable debugging in the lab, modifying hardware, building test fixtures, and communicating tradeoffs clearly across disciplines.
