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Handshake AI Fellowship · United States

Electrical Engineering Expert

part timePosted 3 days ago
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Opportunity Overview

Handshake is looking for experienced electrical and computer engineers to support AI research through flexible, part-time contract work. This is not a traditional job — you'll draw on your hands-on industry experience in power systems, semiconductors, or embedded/RF design to evaluate AI-generated content and provide feedback that helps AI reason like a practicing engineer.

This is an ongoing, project-based opportunity you can take on alongside your current role.

What You'll Do

- Use your industry expertise to create expert-level engineering problems and scenarios grounded in real design, test, and field work

- Review and evaluate AI-generated responses for technical accuracy, practical feasibility, and alignment with how the work is actually done

- Provide structured written feedback to help improve AI model performance

- Complete tasks at your own pace with no set schedule or minimum hour requirement

Qualifications

Ideal candidates meet all three of the following:

- Industry experience — 2+ years of hands-on EE work in industry

- Degree — MS or PhD in Electrical, Electronics, or Computer Engineering. A BS in EE also qualifies when paired with strong industry experience

- Sub-domain depth — demonstrated expertise in one of the following areas:

- Power systems, microgrids, or high-voltage engineering

- Semiconductors, chip design, or EDA

- Embedded systems, DSP, or RF

Additional Qualifications (not Required, But Strengthen Your Application)

- Proficiency with industry tools such as MATLAB/Simulink, Python, SPICE, PSCAD, ETAP, PSS®E, Cadence, Synopsys, Altium, KiCad, Verilog/SystemVerilog, or comparable EDA and simulation environments

- Experience at a recognized EE/hardware employer (e.g. Qualcomm, TI, Intel, NVIDIA, GE, Siemens)

Required For All Applicants

- Based in the United States or Canada

- Strong written communication, attention to detail, and the ability to work independently in a remote, asynchronous environment

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