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OpenAI's Robotics team is seeking a Compute Electrical Engineer to develop AI inference compute systems for humanoid robots. This role sits at the intersection of compute architecture, high-speed digital design, power electronics, and advanced PCB development, requiring ownership across the full hardware lifecycle from concept through production deployment.
You will own compute hardware architecture and development, including component selection, schematic design, PCB layout, validation, and deployment. Key responsibilities include designing and integrating high-speed interfaces (PCIe, DDR, Ethernet, MIPI, USB, DisplayPort) while balancing bandwidth, connectivity, power, and signal integrity. You'll develop onboard DC-to-DC conversion and power distribution systems to meet efficiency, transient-response, sequencing, and power-integrity requirements.
You will define HDI PCB stackups, dielectric materials, via structures, and routing strategies that balance electrical performance, manufacturability, reliability, and cost. Leading bench bring-up and validation is central to the role—this includes test planning, high-speed interface characterization, power measurements, and debugging through verified resolution. You'll partner closely with thermal, mechanical, EMC, and software teams to integrate compute hardware into tightly constrained robotic systems.
The ideal candidate is self-driven, enjoys hands-on engineering, and takes ownership from concept through deployment. You should be comfortable bringing up boards, characterizing interfaces, and tracking challenging failures to root cause.
REQUIREMENTS:
- 5+ years of experience developing compute hardware or similarly complex high-speed electronics, with demonstrated ownership of complete designs
- Strong hands-on measurement and debugging skills, including practical experience with oscilloscopes, probing techniques, and interface validation
- Deep understanding of high-speed digital interfaces sufficient to make architectural tradeoffs and diagnose issues across hardware and software boundaries
- Strong signal-integrity and power-integrity fundamentals, solid foundation in power electronics, and practical experience designing complex HDI PCBs
- Ability to use Linux shell, write simple shell scripts, connect over SSH, and perform basic Ethernet and network troubleshooting
- Initiative and ability to turn ambiguous requirements into concrete engineering plans and deliver working systems
PREFERRED QUALIFICATIONS:
- Experience designing around AI inference SoCs or accelerators, including their power, memory, and communication architectures
- Familiarity with how AI inference workloads map to silicon capabilities, including compute throughput (TOPS), DRAM bandwidth and capacity, and how workload requirements and DRAM technology choices affect achievable performance and performance per watt
- Experience bringing compute hardware into production and resolving fabrication, assembly, or test issues with manufacturing partners
