Electrical Engineer

Electrical engineering for AI research

Help researchers improve model reasoning in circuit analysis and design, power systems and electronics, embedded hardware and control systems. Practical industry judgment is central to the training data and evaluation work.

Technical contributions

• Design demanding engineering tasks and write correct, structured reference solutions.
• Review tasks and model answers for flawed assumptions, unit or sign mistakes, breached design limits and unsafe engineering choices.
• Give precise written feedback that explains the technical basis for each finding.
• Develop assessment guidance for analog and mixed signal circuits, radio frequency work, PCB and board design, power distribution, signal processing and controls.
• Coordinate with other specialists to keep the quality of training data consistent.

Engineering qualifications

A bachelor’s degree or higher in electrical engineering, electrical and computer engineering or a closely related discipline is required. You need at least 5 years of hands on industry work, with relevant settings including semiconductors, consumer electronics, power or utilities, aerospace and defense, automotive and electric vehicles, robotics, telecommunications or medical devices.

You should have owned real engineering outcomes such as circuit or board design and bring up, simulation, power specifications, or hardware progression through reviews, validation and production.

Working familiarity with tools such as SPICE or LTspice, Cadence, Altium, KiCad, MATLAB or Simulink, or ETAP is needed. Relevant standards may include IEEE, NEC, IPC or UL.

Professional skills

Clear progression toward senior or lead responsibility is expected. A professional engineering license is helpful but optional.

You must already use large language models in professional work and be able to recognize incorrect reasoning even when an answer appears convincing. Strong writing is necessary to explain complex design choices clearly.

Employment and schedule

Work is remote within the United States, with applicants in the San Francisco Bay Area strongly preferred. The initial engagement lasts 3 to 4 months, with a strong possibility of continuation, and requires 40 hours each week during weekdays.

This is W2 employment through an employer of record partner, with the opportunity to work in an AI laboratory’s extended workforce. Payroll and benefits are administered by the employment partner.