Senior Software Engineer – Fabrication Data Mining & Analysis Tools (m/f/d)

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 and the future of AI infrastructure
• 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 founders, including CEO Dr. Michael Förtsch, and advisory board members who shaped the semiconductor industry (ARM, Intel, Infineon)
• 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

Your mission

The future of AI computing is light, not electrons.

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.

As a Senior Software Engineer – Fabrication Data Mining & Analysis (m/f/d), you will play a key role in transforming complex fabrication data into a living, scalable, and user-friendly data platform. Your work will directly support our photonics Integrated Circuit (PIC) manufacturing teams by enabling deeper insights into process parameters, material behavior, and device performance across the full value chain—from wafer to NPU.

Your Impact & Responsibilities

• Drive the further development of Q.ANT’s in-house fabrication database into a robust, production-ready platform
• Design, build, and maintain an intuitive graphical user interface (GUI) tailored to user needs across multiple teams
• Develop data mining and analysis tools to identify correlations between fabrication process parameters and physical device behavior
• Enable automated traceability of process steps, results, and deviations across the full manufacturing value chain
• Act as the primary interface for database-related topics, troubleshooting, and continuous improvement
• Collaborate closely with cross-functional stakeholders (manufacturing, physics, engineering, and data teams)
• Translate complex technical concepts into clear, understandable insights for non-expert users

What makes this role unique

• High degree of ownership and freedom: You will independently shape the architecture, workflows, and solutions for our in-house fabrication database and analysis tools.
• Creative problem-solving: You will design tailored data mining and analysis approaches for diverse, real-world fabrication use cases.
• Cross-functional impact: Your solutions will be used by engineers from different disciplines, making your work highly visible and business-critical.
• End-to-end perspective: You will enable traceability of successes and failures across the entire manufacturing process, contributing directly to product quality and scalability.

Technical Skills

• Strong programming skills in Python
• Solid experience with SQL and database design
• Experience with user management and access control systems
• Experience developing user-facing tools or GUIs is highly desirable
• Experience developing Web-based UI for data visualization and analysis platform as you will be incharge of design and implementation of web interfaces for fabrication data exploration

Languages

• Fluent in English (written and spoken)
• German or another European language is a plus

Education & Experience

• Master’s degree in Data Science, Computer Science, Engineering, or a related field
• Background or strong interest in physics, semiconductor manufacturing, or photonics is a strong advantage
• Proven experience in building, managing, and scaling databases and data platforms
• Hands-on experience in data mining, data analysis, or applied data science
• Experience working with interdisciplinary teams and managing diverse technical requirements

Ways of Working

• Very high level of self-leadership and ownership
• Strong solution-oriented mindset with the ability to prioritize and structure complex topics
• Excellent communication and collaboration skills across technical and non-technical audiences
• High curiosity, intrinsic motivation, and willingness to explore cross-correlations in complex data sets