Deepika Kanade is a Lead Research Engineer with 8 years of experience building production-ready computer vision and ML systems, currently driving MLOps, instance segmentation and pose-estimation work at Siemens from Bengaluru. She holds an M.S. in Electrical Engineering (specializing in ML and CV) from USC and has a strong track record of shipping embedded vision software and quantization-aware inference optimizations from roles at Ambarella and research labs. Her strengths span end-to-end feature development, synthetic data generation with Blender, USD-based 3D world manipulation, and Kubeflow/Kubernetes pipelines for deploying models to diverse customer data. Deepika has repeatedly translated state-of-the-art research into practical systems—achieving SOTA quantized ImageNet results and adapting SLAM and perception modules for real-world mapping and bin-picking. Known for mentoring interns and managing scrum for mid-sized projects, she blends hands-on engineering with research rigor and an eye for realistic simulation-driven data generation.
8 years of coding experience
5 years of employment as a software developer
Master's degree Electrical Engineering, Master's degree Electrical Engineering at University of Southern California
Bachelor of Engineering (BE) Electronics and Telecommunication Engineering, Bachelor of Engineering (BE) Electronics and Telecommunication Engineering at Maharashtra Institute of Technology
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