Overview:
Overview:
Senior hands-on individual contributor responsible for enabling enterprise Vision Intelligence capabilities across Computer Vision, Vision-Language Models (VLMs), Vision Agents, Edge AI and IoT. Partners with Domain and Enterprise Architecture teams to translate business needs and architecture patterns into scalable, production-ready capabilities.
Responsibilities:
Key Responsibilities:
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Serve as the technical SME for Vision Intelligence, covering CV, VLMs, Vision Agents, Edge AI and IoT.
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Design, train, evaluate and productionize CV models for detection, classification, segmentation, tracking, OCR, anomaly detection and activity recognition.
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Develop VLM and multimodal solutions for image/video understanding, visual reasoning and operational intelligence.
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Build Vision Agents combining visual intelligence, IoT telemetry, enterprise context, tools and workflows.
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Enable reusable platform capabilities including inference services, APIs, SDKs, model pipelines and reference implementations.
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Deploy and optimize AI workloads across edge GPUs, industrial PCs, smart cameras and cloud/edge environments.
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Integrate cameras, sensors and IoT/OT systems using RTSP, ONVIF, MQTT, OPC UA and related technologies.
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Establish Vision MLOps practices for datasets, evaluation, CI/CD, deployment, monitoring and model drift.
Partner with Manufacturing, Warehouse, Quality, EHS and other domains to move solutions from POC Pilot Production- Scale.
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Evaluate emerging CV, VLM, Edge AI, Vision Agent and Physical AI technologies through hands-on prototyping and benchmarking.
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Collaborate with Domain and Enterprise Architects and mentor engineering teams on Vision Intelligence implementation.
Qualifications:
Qualifications:
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Overall 10+ years of overall experience is required.
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Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience)
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8–12+ years of AI/software engineering experience, including 5+ years in Computer Vision/Vision AI.
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Strong hands-on experience developing and deploying production-grade CV models and real-time video analytics.
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Practical experience with VLMs, multimodal AI and Vision Agents.
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Experience with PyTorch, OpenCV, YOLO, ONNX, TensorRT, NVIDIA DeepStream or equivalent technologies.
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Experience deploying AI on GPU/edge platforms, containers and Kubernetes/K3s.
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Strong IoT/OT integration experience with cameras, sensors, gateways and industrial environments.
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Experience with CV/Vision MLOps, model optimization, evaluation and production monitoring.
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Demonstrated experience taking Vision AI solutions from prototype through production at multiple sites.
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Manufacturing, warehouse, supply-chain, quality, EHS, robotics or industrial automation experience is highly desirable.
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Exposure to Digital Twins, sensor fusion, robotics and Physical AI is a plus.
