AI Measurement Architect

About us:
Axiomatic AI is building a new class of AI systems designed to reason with the rigor of the scientific method. By combining deep learning with formal logic and physics-based modeling, we create verifiable, interpretable AI systems that collaborate with and support human researchers in high-stakes scientific and engineering workflows.
Our mission, 30×30, is to deliver a 30× improvement in the speed, accessibility, and cost of semiconductor and photonic hardware development by 2030.
We aim to revolutionize hardware design and simulation in these industries and are building a team of highly motivated professionals to bring these innovations from research into commercial products.
Position overview
We are seeking an AI Measurement Architect to design the intelligent automation layer of our measurement systems for electro-optic, RF analog, and quantum devices.
Working closely with the Optoelectronic Measurements & AI Lead Systems Engineer, you will architect agent-driven workflows, adaptive experimentation strategies, and data-model feedback loops that accelerate device characterization across die, wafer, package, and board levels.
Your focus will be on building the reasoning, learning, and optimization infrastructure that transforms traditional measurement pipelines into autonomous, adaptive systems.
Responsibilities
Architect measurement systems that combine agentic reasoning, feedback control, and statistical inference to autonomously characterize semiconductors at the die, wafer, package, and board levels.
Partner with the Lead Systems Engineer to integrate intelligent control architectures into the broader AX-Measure platform.
Develop active learning and Bayesian optimization routines that navigate high-dimensional parameter spaces for rapid characterization
Implement system identification and physics-informed ML techniques for measurements
Define experimental protocols for novel technologies (e.g., qubit readout, RF linearity, photonics) and convert them into executable agentic tasks.
Build workflows that compare real-time measurement data against simulation models
Create self-healing routines that autonomously detect calibration drift, diagnose instrument faults, and re-optimize measurement strategies
Requirements
M.S., PhD in Engineering (electrical, computer, mechanical) or Applied Physics, or a closely related field
3+ years of experience in quantum technologies, semiconductor process control, photonics, or related domains
3+ years of experience in semiconductor design-fab-test flows and design-measurement feedback loops
5+ years of experience in low frequency, high-frequency, and precision measurements and instrument control at die, wafer-scale, package, and board levels
2+ years experience in PyData stack (NumPy, SciPy, Pandas)
Hands-on experience with high frequency, low-noise, and/or electro-optic measurements
Familiarity with Gaussian processes, Bayesian inference, or optimal experimental design
Nice to have
Experience with agentic frameworks and tooling, such as Pydantic AI, LangChain, MCP-based tools/servers, or similar systems
Experience with EDA tools (e.g., Keysight ADS, Cadence, Klayout) and design flows
Experience with robotics and physical AI
Publication record in autonomous experimentation and self-driving labs
High agency: self-starter, no task too large or too small attitude.
What we offer:
Competitive compensation
Stock Options Plan: Empowering you to share in our success and growth.
Cutting-Edge Tools: Access to state-of-the-art tools and collaborative opportunities with leading experts in artificial intelligence, physics, hardware and electronic design automation.
Work-Life Balance: Flexible work arrangements in one of our offices, and sponsored visit to other Axiomatic Offices around the world.
Professional Growth: Opportunities to attend industry conferences, present research findings, and engage with the global AI research community.
Impact-Driven Culture: Join a passionate team focused on solving some of the most challenging problems at the intersection of AI and hardware.