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Specialized senior role at a known engineering firm in a metro city, moderate applicant density.
High because role requires niche edge-AI, embedded hardware, and vertical domain experience.
High due to mandatory niche edge-AI, embedded systems, and hardware-acceleration expertise.
Lead the end-to-end technical delivery of Edge AI, Computer Vision, and Generative/Agentic AI solutions on embedded, edge, and on-premise platforms.
Drive architecture, delivery planning, benchmarking, optimization, and integration of AI systems with sensors, cameras, and industrial devices under resource constraints (<4GB RAM, <10W power).
Own delivery schedules, manage technical risks, and lead Agile/Hybrid co-development projects ensuring compliance with safety and regulatory standards.
Deep expertise in Computer Vision techniques (CNNs, object detection, segmentation, vision transformers).
Proven experience deploying and optimizing AI models on resource-constrained edge devices using frameworks like TensorFlow Lite, ONNX Runtime, OpenVINO, TensorRT, or PyTorch Mobile.
Strong programming skills in Python and C/C++ with knowledge of CUDA/OpenCL for GPU acceleration; familiarity with embedded systems and sensor integration.
Work Experience Required: Not explicitly mentioned in the JD; Bachelor's degree mandatory, Master's preferred in Computer Science, Software Engineering, or related fields.
Experienced in at least one targeted industry vertical: Manufacturing (industrial automation, ISO 9001), Medical Diagnostics (imaging modalities, FDA regulations), or Automotive (ADAS, ISO 26262).
Operates effectively in complex hardware-software co-development environments involving edge AI inference optimization and multi-sensor integration.
Strategically proficient in designing hybrid AI systems combining local edge and centralized services, and managing technical delivery under strict resource and regulatory constraints.