Lab Software Automation Engineer (m/f/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.

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Source: Statistisches Bundesamt (Destatis), table; dl-de/by-2-0; StarIn's calculation