Product Management, Algorithms, V (E5)

1. Lead AI Strategy Across Reconstruction and Internal Modeling Drive the development, integration, and deployment of our AI-driven reconstruction capabilities. Partner with academic collaborators to advance cutting-edge research and translate findings into production‑grade algorithms. Architect and deliver a robust, intuitive interface enabling users to perform pair-wise dataset training and generate updated model versions with minimal ML expertise. Participate in customer visits, technology reviews, technical deep dives, and roadmap discussions. Provide strategic input on hardware/software co‑design for future product generations. Collaborate closely with product management and remote workforce on software and algorithm engineering. Contribute to internal standards, documentation, and repeatable workflows for model training, validation, and deployment. PhD or MS in Computer Science, Electrical Engineering, Physics, Applied Mathematics, or a related field. 5+ years of industry or postdoctoral experience in AI/ML for imaging, reconstruction, or scientific computing. Neural networks for image restoration/reconstruction (e.g., U-Net, GANs, diffusion), Classical and physics-informed reconstruction pipelines (e.g., FBP/FDK, iterative reconstruction, sinogram-domain optimization), Multimodal or hybrid-domain reconstruction. Strong proficiency in Python, PyTorch/TensorFlow, and scientific computing frameworks. Experience developing tools enabling user‑driven ML training. Familiarity with semiconductor manufacturing processes, inspection requirements, and metrology constraints. Prior customer‑facing technical roles or experience supporting high-value accounts. Experience with GPU optimization, model deployment pipelines, or large-scale data handling.