Optoelectronic Measurements & AI Lead Systems Engineer (Semiconductors)

TL;DR

Optoelectronic Measurements & AI Lead Systems Engineer (Semiconductors): Define and deploy robust semiconductor measurement architectures that integrate instrumentation control, data infrastructure, and AI-enabled optimization for production-ready workflows. Focus on agentic AI applications in high-stakes physical experimentation, system-level KPIs like throughput and data integrity, and seamless integration with customer hardware and EDA tools.

Location: Toronto, Canada (flexible work arrangements in one of our offices)

Company

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

What you will do

• Define end-to-end system architecture for AI agents interfacing with hardware, data infrastructure, and EDA workflows.
• Lead technical integration of subsystems including instrument drivers, algorithms, and database layers for fault-tolerant products.
• Specify and drive system-level KPIs such as measurement throughput, latency, thermal stability, and data integrity.
• Serve as primary technical contact for customers, translating requirements into engineering tasks and leading deployments.
• Gather user feedback to inform product roadmap and prioritize R&D; drive integration with measurement software and design tools.
• Establish best practices for agentic AI in manufacturing environments and define scalable product interfaces.

Requirements

• M.S. or PhD in Engineering (electrical or mechanical), Applied Physics or equivalent.
• 7+ years hands-on engineering experience, including 3+ years in system-level or customer-facing roles.
• 5+ years in quantum technologies, semiconductor process control, photonics, or related domains.
• 3+ years in automation of measurements and data analysis; deep familiarity with semiconductor test flows (WAT, reliability testing, electro-optic characterization).
• Experience leading small cross-functional teams (code review, timelines, architecture).
• Familiarity with machine learning or AI applied to scientific/engineering problems; strong communication across research, product, and industry.

Nice to have

• Experience with semiconductor companies, foundries, and R&D partners.
• Formal systems engineering methodologies; agentic AI frameworks.
• High-volume manufacturing; autonomous experimentation or self-driving labs.
• Track record translating research into deployed products; modern software best practices.

Culture & Benefits

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