We partner with the world's leading AI research labs to build smarter, more capable AI models — and we need electrical engineers to help get there. Your deep technical knowledge will be used to stress-test advanced language models, expose their reasoning gaps, and help shape how AI understands complex engineering concepts.
This is a rare opportunity to work at the intersection of engineering and artificial intelligence — no prior AI experience required.
Design Challenging Problems — Craft advanced electrical engineering problems spanning circuit analysis, power systems, signal processing, electromagnetics, and control systems to expose the limits of AI reasoning
Author Gold-Standard Solutions — Develop rigorous, step-by-step solutions that serve as benchmarks for AI learning and evaluation
Audit Technical Accuracy — Review AI-generated outputs including code, circuit diagrams,
and mathematical proofs for correctness, safety, and alignment with standards such as IEEE and NEC
Sharpen AI Reasoning — Identify logical flaws in AI-generated engineering reasoning and provide structured, actionable feedback to improve model performance
Document Failure Modes — Record how and where AI models fall short so research teams can systematically harden model capabilities
Who You Are
Pursuing or holding a Master's or PhD in Electrical Engineering, Electronic Engineering, or a closely related field
Strong foundational knowledge in one or more core domains: VLSI, control systems, telecommunications, power electronics, or signal processing
Able to communicate complex technical concepts clearly and concisely in written form
Detail-oriented with high precision when working with mathematical equations, circuit logic, and technical documentation
Self-motivated and comfortable working independently on an async, adaptable sch
📌 Electrical Engineering (Ciudad de México)
🏢 Alignerr
📍 Ciudad de México
Postulate a este anuncio
Muestra tus habilidades a la empresa, rellenar el formulario y deja un toque personal en la carta, ayudará el reclutador en la elección del candidato.