Serviceability Engineer - Software & AI

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The Customer Services Molecular Imaging (CS MI) Service Engineering department at Siemens Healthineers delivers industry‑leading serviceability and lifecycle support for Molecular Imaging systems by working in parallel with clinical product development to ensure service readiness at product launch and beyond, including training, technical documentation, diagnostics, spare parts, and serviceability requirements. The organization continuously enhances service methodologies and digital capabilities for the global installed base, driving service productivity, quality, and customer satisfaction throughout the product lifecycle. As part of the Serviceability Engineering team, this role is instrumental in advancing the digital transformation of how complex SPECT/CT systems are maintained and serviced, bridging traditional mechanical and systems engineering with modern software, AI‑driven automation, and augmented reality solutions, while laying the groundwork for future robotics and automation strategies that empower field teams and enable scalable, digital‑first service excellence.

Customer Services Molecular Imaging (CS MI) Service Engineering Department

The CS MI Service Engineering department is committed to providing industry-leading serviceability features and support for field personnel. The team consists of project managers, product technical engineers, authors, and content management specialists who work collaboratively and in parallel with clinical product development processes. Their integrated approach ensures the availability of essential training materials, technical documentation, service parts, and serviceability requirements for the initial delivery of new products.

In addition to supporting new product launches, the department maintains and updates content for products in the installed base, continuously developing innovative service methodologies to achieve service productivity goals. Through proactive collaboration and a focus on excellence, MI Service Engineering empowers field teams with the resources and expertise needed to deliver outstanding service throughout the product lifecycle.

As part of the serviceability engineering team at Siemens Healthineers, this role is critical in driving the digital transformation of how complex medical imaging equipment (SPECT/CT) is maintained and serviced. You will bridge the gap between traditional mechanical engineering and modern software architecture, focusing on the development of digital solutions (Agentic AI, Augmented Reality, Software Automation) and the foundational work required for future strategic implementations (ie. Robotics & Automation).

Key Responsibilities and Expectations

• AI Development: Collaborate with hardware subject matter experts and data scientists to design, write, and deploy automated workflow/diagnostics scripts and self-healing algorithms that will be utilized in servicing MI equipment.
• System Integration: Develop secure, reliable APIs and communication protocols to link on-premise imaging equipment with cloud-based AI orchestrators and spatial computing interfaces (AR/VR headsets).
• Process Automation: Analyze existing text-based service manuals and diagnostic trees, converting manual troubleshooting steps into executable code and automated workflows.
• Cross-Functional Collaboration: Act as the software liaison within a hardware-centric team, translating software architecture concepts to mechanical engineers and interpreting machine physics into algorithmic logic.
• Participate actively in cross-functional projects & delivering assigned service features.
• Demonstrate a strong commitment to service quality by actively participating in decision-making processes and prioritizing customer needs throughout all project phases.

Qualifications for success in this role

• Education: A recent Bachelor’s or Master’s degree in Computer Science, Robotics, Software Engineering, Mechatronics, or a closely related technical discipline.
• Programming Proficiency: Strong, demonstrable experience writing clean, production-ready code in Python and C++.
• AI/ML Foundations: A solid conceptual understanding of Machine Learning frameworks (PyTorch, TensorFlow), Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Reinforcement Learning.
• Development Tools: Experience with version control, API development,