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Specialized CV skills reduce applicants though 3-6 years requirement and Pune metro increase competition.
Strong computer vision and edge inference specialization limits cross-industry transferability.
Explicit 4+ years, production CV experience and mandatory inference optimization tech impose strict filters.
Own the end-to-end lifecycle of detection, tracking, and re-identification models processing live video from thousands of cameras in real deployment environments.
Design, train, and optimize models to run efficiently on edge and on-premise GPUs with techniques like TensorRT, ONNX, and quantization.
Develop evaluation pipelines to measure real-world accuracy and collaborate with deployment engineers to fine-tune models for customer-specific camera setups and scenes.
4+ years of professional experience in computer vision or deep learning with proven production model deployment.
Strong programming skills in Python and PyTorch with deep knowledge of modern detection and tracking architectures.
Experience in optimizing inference for real-time applications in resource-constrained environments.
Work Experience Required: 4+ years in computer vision / deep learning with production models shipped.
Technical expert comfortable bridging research models to running production on real-world edge devices under operational constraints.
Experienced in hands-on model optimization and tuning for live video analytics in critical, high-stakes environments.
Operates with a pragmatic approach prioritizing real-world field performance over just benchmark metrics.