We're partnering with the world's leading AI research labs to build smarter, more capable AI models — and we need electrical engineers to make it happen.
As an AI Data Trainer, you'll stress-test advanced language models on real engineering problems, expose their blind spots, and help shape how AI reasons through complex technical challenges.
This is a unique opportunity to apply your deep domain expertise to one of the most impactful fields in technology today — on your own schedule, from anywhere in the world.
Why Join Us
Work on cutting-edge AI projects alongside world-class research teams.
Fully remote and flexible — work when and where you choose.
Freelance perks: autonomy, variety, and global collaboration.
Direct exposure to how advanced large language models are built and trained.
Potential for ongoing work and contract extension.
Responsibilities
Design Challenging Problems — Create advanced electrical engineering problems spanning circuit analysis, power systems, signal processing, electromagnetics, and control systems to push AI to its limits.
Author Ground-Truth Solutions — Develop rigorous, step-by-step solutions and benchmark responses that AI models learn from and are evaluated against.
Audit Technical Accuracy — Review AI-generated outputs including code, circuit diagrams, and mathematical proofs for correctness, safety, and compliance with engineering standards (IEEE, NEC, etc.).
Refine AI Reasoning — Identify logical errors and flawed reasoning in AI responses, then provide structured feedback to improve how the model thinks through engineering tasks.
Work Asynchronously — Manage your own workload and schedule with full flexibility.
Required skills
Strong foundational knowledge in one or more core EE domains — VLSI, control systems, telecommunications, power electronics, signal processing, or embedded systems.
Able to communicate complex technical concepts clearly and precisely in writing.
Detail-oriented with a sharp eye for mathematical and logical accuracy.
Self-motivated and comfortable working independently.
Preferred skills
Experience with data annotation, technical writing, or quality evaluation.
Familiarity with simulation tools (MATLAB, SPICE, etc.).
Background in academic research or technical publishing.
Experience and education
Pursuing or holding a Master's or PhD in Electrical Engineering, Electronic Engineering, or a closely related field.
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.