Measurement Software Engineer
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 a Measurement Software Engineer to design and implement the software backbone of AX-Measure, the control layer powering our autonomous lab platform.
In this role, you will build robust, production-grade systems that translate high-level AI decisions into precise, safe, and verifiable hardware commands. Your software will control millions of dollars of laboratory equipment, orchestrate parallel experimental workflows, and ensure that our self-driving lab operates reliably under real-world conditions.
You will work closely with the AI Measurement Architect and the Optoelectronic Lead Systems Engineer to operationalize measurement strategies into scalable, fault-tolerant software infrastructure
Responsibilities
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Design and implement unified APIs and SDKs enabling AI agents to control diverse laboratory instruments (oscilloscopes, network analyzers, SMUs, signal generators, lasers, etc.)
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Build high-concurrency execution engines to orchestrate parallel measurements across multiple wafer chucks, cryostats, or test stations
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Architect scalable data ingestion pipelines and storage systems capable of handling high-frequency data streams and making them immediately queryable for AI models
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Implement guardrail logic and runtime validation layers to prevent unsafe hardware operations and verify AI-generated commands
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Develop fault-tolerant and observable systems with structured logging, monitoring, failure handling, and safe degradation mechanisms
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Integrate measurement outputs with modeling and analysis frameworks to enable closed-loop semiconductor and photonic development
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Requirements
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B.S. or M.S. in Electrical Engineering, Computer Engineering, Computer Science, or related field
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4+ years of experience building production-grade software systems
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Strong Python engineering experience (packaging with Poetry/UV, type hinting, decorators, context managers, modular architecture)
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Experience automating laboratory or industrial hardware via VISA, SCPI, TCP/IP, gRPC, or similar protocols
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Experience designing and maintaining SDKs, APIs, or control frameworks
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Experience with structured scientific data formats (e.g., HDF5) and/or time-series databases
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Experience building concurrent and asynchronous systems
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Demonstrated experience building reliable systems where hardware safety, financial cost, or operational integrity are at stake
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Nice to Have
- Experience with Rust or C++ for performance-critical loops
- Familiarity with containerization (Docker) for deploying measurement runtimes
- Hands-on experience in electro-optic measurements of bare dies, wafers, packaged chips, and boards
- Experience with concurrent and asynchronous software systems, software testing and reliability, and production-grade robustness (observability, failure handling, safe degradation)
- 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.
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