Lab Software Automation Engineer (m/f/d)

Your mission The future of AI computing is light, not electrons. As Lab Software Automation Engineer (m/f/d), you will bring strong software engineering expertise directly into our lab environment. You will bridge the gap between R&D bringup and operations, equipping our teams with the software tools, routines, and automation needed to efficiently perform complex measurements and hardware testing. By embedding a "data-first" and software-driven mindset into the lab, you will ensure high-quality deliverables and enable the seamless transition of our photonic NPUs from R&D to full production. At Q.ANT, we are building photonic processing systems that compute with light—delivering a scalable, energy-efficient alternative to transistor-based architectures for next-generation AI and high-performance computing. Your Impact & Responsibilities Drive Lab Automation: Define measurement strategies, develop robust measurement routines, and automate software tasks across bringup and operations to streamline production workflows. Bridge Bringup & Operations: Serve as the central technical connection between R&D systems engineering, bringup teams, and operations, ensuring high dependability and on-time NPU deliveries (OTIF). Enable Data Analytics: Lead data-gathering efforts and manage long-term database storage to provide actionable insights for R&D and key stakeholders. Optimize Software Protocols: Establish clear software protocols, best practices, and documentation for lab tasks, while consulting on and developing internal lab software tools. Solve Complex Lab Challenges: Work autonomously to investigate and resolve complex measurement or hardware bringup issues using structured software engineering principles. Scale Internal Capabilities: Over time, expand automation systems to connect with backend operational databases and explore cross-reusability of software tools within R&D. Your profile Education: B.Sc. or M.Sc. in Computer Science, Electrical Engineering, Physics Software Core: Solid foundation in software engineering principles and hands-on proficiency in Python. Lab & Automation Focus: Strong interest or experience in lab automation, IT automation, or signal processing. Data & Tooling: Familiarity with modern software workflows (e.g., GitHub Flow) and interest/experience with databases and data visualization tools. Mindset: Highly analytical, solution-oriented, with strong ownership and self-leadership skills to drive processes forward independently. Experience Level: Open to both promising entry-level candidates with strong relevant foundations and experienced specialists/experts. Prior lab experience and exposure to lab automation frameworks (e.g., LabVIEW or similar tools) is a plus! Why us? Work on the leading edge: Photonic AI acceleration technologies that will define the next decade of computing - already validated in production HPC environments. Make impact at scale: Help solve one of computing's biggest challenges—making growing demand in compute and sustainability go hand in hand. Own your work from day one: Broad autonomy and decision authority with direct impact on product success, production efficiency, and overall NPU quality. Fast-track your growth: Work on challenges with few industry precedents—every problem you solve becomes new institutional knowledge and potentially industry-defining IP. World-class team: Collaborate alongside a passionate, international, cross-functional team of experts in photonics, processor design, and AI systems. Direct access to leadership: Work closely with the company's leaders, including VP SW and founders, within a transparent and fast-moving structure. Collaborative culture: Innovative work environment that values technical excellence, open communication, and pragmatic problem-solving. Be part of history: Join at the inflection point where photonic computing transitions from research to mainstream—your contributions will shape this transformation. About us Who we are and what we do Q.ANT is a deep-tech scale-up developing photonic processing solutions that compute natively with light and deliver a scalable alternative to transistor-based systems. The analog co-processors are optimised for complex computations and enable energy-efficient performance for next-generation AI and HPC applications. In collaboration with the Institute for Microelectronics Stuttgart IMS CHIPS, Q.ANT operates its own pilot line for photonic chips, based on the material system Thin-Film Lithium Niobate TFLN. Q.ANT was founded by Michael Förtsch in 2018 and is headquartered in Stuttgart, Germany.