AI Measurement Architect

TL;DR

AI Measurement Architect (AI/Hardware): Architecting intelligent automation layers for measurement systems in electro-optic, RF analog, and quantum devices with an accent on agent-driven workflows, adaptive experimentation, and data-model feedback loops. Focus on building reasoning, learning, and optimization infrastructure to transform traditional pipelines into autonomous adaptive systems for semiconductor characterization at die, wafer, package, and board levels.

Location: Toronto, Canada. Flexible work arrangements in one of our offices.

Company

hirify.global builds verifiable, interpretable AI systems combining deep learning, formal logic, and physics-based modeling to accelerate semiconductor and photonic hardware development.

What you will do

• Architect measurement systems using agentic reasoning, feedback control, and statistical inference for autonomous semiconductor characterization across die, wafer, package, and board levels.
• Integrate intelligent control architectures into the AX-Measure platform with the Lead Systems Engineer.
• Develop active learning and Bayesian optimization for navigating high-dimensional parameter spaces.
• Implement system identification and physics-informed ML for measurements.
• Define experimental protocols for novel technologies like qubit readout, RF linearity, photonics, and convert to agentic tasks.
• Build workflows comparing real-time measurement data against simulation models.
• Create self-healing routines to detect calibration drift, diagnose faults, and re-optimize strategies.

Requirements

• M.S. or PhD in Engineering (electrical, computer, mechanical) or Applied Physics, or related field.
• 3+ years in quantum technologies, semiconductor process control, photonics, or related domains.
• 3+ years in semiconductor design-fab-test flows and design-measurement feedback loops.
• 5+ years in low/high-frequency, precision measurements, and instrument control at die, wafer, package, board levels.
• 2+ years with PyData stack (NumPy, SciPy, Pandas).
• Hands-on experience with high frequency, low-noise, electro-optic measurements.
• Familiarity with Gaussian processes, Bayesian inference, or optimal experimental design.

Nice to have

• Experience with agentic frameworks like LangChain or similar.
• Experience with EDA tools (Keysight ADS, Cadence, Klayout).
• Experience with robotics and physical AI.
• Publication record in autonomous experimentation and self-driving labs.

Culture & Benefits

• Competitive compensation and stock options.
• Access to cutting-edge tools and collaboration with AI, physics, hardware experts.
• Flexible work in offices with sponsored visits to other offices worldwide.
• Opportunities for conferences, research presentations, and global AI community engagement.
• Impact-driven culture solving AI-hardware challenges.