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 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 optical 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 visits 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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