Summary
Dipanjan Das is a Senior AI Engineer based in Berlin with nine years of experience building production-grade embedded and perception systems for automotive and security applications. He specializes in deep learning for radar point clouds, distributed radar architectures, and real-time ML inference optimization for ADAS and autonomous driving. His background spans low-level embedded C/C++ work, integration of multi-language stacks, and CI/CD and package management for automotive ECUs, reflecting a rare blend of systems engineering and model-level optimization. At Xavveo he leads AI perception and simulation efforts to train and validate dense, all-weather 360° sensing, having previously driven quantization and inference projects at CARIAD. Earlier roles at TeamViewer combined fraud-detection ML, user-facing security features and AR-enabled mobile work, showing a strong applied ML pedigree beyond pure research. Colleagues know him as a pragmatic tinkerer—“retrying stuffs everyday”—who turns complex data and hardware constraints into deployable, safety-focused solutions.
9 years of coding experience
10 years of employment as a software developer
Master of Science (M.Sc.) Electrical Engineering and Information Technology(Major Communications Engineering), Master of Science (M.Sc.) Electrical Engineering and Information Technology(Major Communications Engineering) at Darmstadt University of Applied Sciences
Bachelor's Degree Electronics and Communications Engineering, Bachelor's Degree Electronics and Communications Engineering at West Bengal University of Technology, Kolkata
High School Science, High School Science at Habra High School
English, German, Bengali, Hindi