Remote Electrical Engineering AI Data Trainer

Alignerr; Sheffield (TX); On-site; USD 55,000 - 124,000; Part time

Benefits offered by this job

Remote work

Flexible hours

Freelance autonomy

Job summary

Alignerr is seeking an Electrical Engineering AI Data Trainer to stress-test language models on advanced engineering problems. You will create challenging tasks, author rigorous solutions, and audit AI outputs to ensure accuracy, safety, and adherence to standards like IEEE/NEC.

The role emphasizes independent work with flexible hours, remote collaboration, and potential for ongoing engagement, drawing on your deep EE domain knowledge.

Qualifications

• Degree in Electrical Engineering; Master's or PhD preferred.
• Deep expertise in core areas: VLSI, control systems, telecommunications, power electronics, signal processing, or embedded systems.
• Clear ability to communicate complex concepts in writing.

Responsibilities

• Design challenging electrical engineering problems spanning circuit analysis, power systems, signal processing, electromagnetics, and more to push AI to its limits.
• Author ground-truth solutions with rigorous, step-by-step technical explanations used as the gold standard for AI learning.
• Audit AI-generated code, circuit diagrams, and proofs for correctness, safety, and standards compliance such as IEEE and NEC.
• Sharpen AI reasoning by identifying logical flaws and providing structured feedback to improve model performance.

Skills

Electrical engineering

VLSI

control systems

telecommunications

power electronics

signal processing

embedded systems

Technical writing

Education

Master's in Electrical Engineering

PhD in Electrical Engineering or related

Tools

MATLAB

SPICE

Job description

Alignerr is seeking an Electrical Engineering AI Data Trainer to stress-test language models on advanced engineering problems. You will create challenging tasks, author rigorous solutions, and audit AI outputs to ensure accuracy, safety, and adherence to standards like IEEE/NEC.

The role emphasizes independent work with flexible hours, remote collaboration, and potential for ongoing engagement, drawing on your deep EE domain knowledge.