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 Design and implement unified APIs and SDKs enabling AI agents to control diverse laboratory instruments (oscilloscopes, network analyzers, SMUs, signal generators, lasers, etc.) Build high-concurrency execution engines to orchestrate parallel measurements across multiple wafer chucks, cryostats, or test stations Architect scalable data ingestion pipelines and storage systems capable of handling high-frequency data streams and making them immediately queryable for AI models Implement guardrail logic and runtime validation layers to prevent unsafe hardware operations and verify AI-generated commands Develop fault-tolerant and observable systems with structured logging, monitoring, failure handling, and safe degradation mechanisms Integrate measurement outputs with modeling and analysis frameworks to enable closed-loop semiconductor and photonic development Requirements B.S. or M.S. in Electrical Engineering, Computer Engineering, Computer Science, or related field 4+ years of experience building production-grade software systems Strong Python engineering experience (packaging with Poetry/UV, type hinting, decorators, context managers, modular architecture) Experience automating laboratory or industrial hardware via VISA, SCPI, TCP/IP, gRPC, or similar protocols Experience designing and maintaining SDKs, APIs, or control frameworks Experience with structured scientific data formats (e.g., HDF5) and/or time-series databases Experience building concurrent and asynchronous systems Demonstrated experience building reliable systems where hardware safety, financial cost, or operational integrity are at stake 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.