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.