AI Trainer - Electrical Engineering

Planet Pharma; United States; Remote; USD 120.000 - 180.000; Vollzeit

Zusammenfassung

Planet Pharma is seeking experienced electrical and electronics engineers to evaluate how frontier AI models perform real engineering tasks, from circuit specification to control loop stabilization and power‑stage sizing. You bring the practical judgment honed by years of designing, debugging, and shipping hardware.

We provide the complex engineering problems the models cannot yet solve. You will design realistic tasks from your practice, run them through frontier AI models, and assess outputs

Qualifikationen

• Experience evaluating AI in hardware contexts.
• Ability to design and critique circuits and systems.
• Strong written communication to justify technical judgments.

Aufgaben

• Design realistic engineering tasks for frontier AI evaluation.
• Assess AI model outputs against professional standards and benchmarks.

Kenntnisse

Electrical engineering

AI model evaluation

Circuit design

Control systems

Ausbildung

Bachelor's degree in EE

Tools

MATLAB/Simulink

Python

Jobbeschreibung

Looking for experienced electrical and electronics engineers to evaluate how frontier AI models handle real engineering work: specifying a circuit, stabilizing a control loop, closing a link budget, sizing a power stage, debugging a signal chain. The models can already talk fluently about electronics; what they cannot yet do reliably is the actual work. You bring the judgment you have built over years of designing, debugging, and shipping hardware. We bring the engineering problems the models cannot yet solve on their own.

This is a new and growing area for our company, focused on teaching AI to reason correctly about circuits, systems, and physical constraints. In this role, you will design challenging, realistic tasks drawn from your own practice, run them through frontier AI models, and evaluate what comes back against a professional standard. Your engineering judgment, your standard for what counts as a correct answer, and the written rationale behind them become the signal that shapes the next generation of engineering tools.

You will work with realistic professional files, the kind a practitioner in your field actually handles, which you assemble yourself. Some tasks are compact, built around a handful of files; others are larger scenarios that take several days to build. In every case the goal is the same: a task a competent professional in your field would complete correctly and a frontier model currently gets wrong.

This is not a traditional electrical engineering role. You will be helping build better AI by putting your knowledge to work in a structured, flexible, fully remote environment. The work is long-form and self-directed, and clear written reasoning matters as much as technical depth.