Your deep domain knowledge will directly shape how AI understands and reasons through complex engineering problems — from circuit analysis to power systems to signal processing.
This is a fully remote, flexible contract role designed to fit around your existing schedule. Whether you're a grad student, a working engineer, or a seasoned professional, your expertise has real value here.
Why Join Us
Work on cutting-edge AI projects alongside top research labs and AI teams.
Fully remote and asynchronous — work on your own schedule, from anywhere.
Freelance perks: full autonomy, flexibility, and global collaboration.
Gain rare, first-hand exposure to how advanced LLMs are trained and evaluated.
Meaningful work — your engineering expertise directly improves AI safety and accuracy.
Potential for ongoing work and contract extension.
Responsibilities
Design challenging problems across core EE domains — including circuit analysis, power systems, signal processing, electromagnetics, control systems, and embedded systems — to rigorously test AI performance.
Author gold-standard solutions by writing detailed, step-by-step technical responses that serve as benchmarks for AI learning.
Audit AI outputs — evaluate generated code, circuit diagrams, and mathematical proofs for correctness, safety, and compliance with engineering standards (IEEE, NEC, etc.).
Improve AI reasoning by identifying logical flaws and providing structured, actionable feedback that helps models think more like expert engineers.
Required skills
Strong foundational knowledge in one or more areas: VLSI, control systems, telecommunications, power electronics, or signal processing.
Able to communicate complex technical concepts clearly and precisely in writing.
Detail-oriented — you catch errors in equations, circuit logic, and technical documentation that others miss.
Preferred skills
Experience with data annotation, data labeling, or evaluation systems.
Familiarity with large language models (LLMs) or AI-generated content review.
Background in simulation tools such as MATLAB, SPICE, or similar.
Experience and education
Pursuing or holding a Master's or PhD in Electrical Engineering, Electronic Engineering, or a closely related field.
No prior AI or data annotation experience required.
Thriveth makes AI data-training work easier to find, understand, and navigate. We replace uncertainty with clear opportunities, realistic expectations, and insights from real application journeys.
Hiring companyAlignerr
Turing