We are looking for a Vision AI Architect to lead the design and implementation of large-scale Vision AI platforms and solutions. The role requires deep expertise across the entire video and vision lifecycle: capture, encoding, transcoding, transport, preprocessing, model development, training, deployment, scaling, application integration, and production operations. You will define reference architectures, guide engineering teams, and lead customer engagements from solution discovery through deployment. Programming Languages & Technology Stack ​ · Expert-level Python, C/C++ or similar core programming languages · Strong experience with PyTorch, TensorFlow, OpenCV, CUDA, NVIDIA ecosystem, and AI acceleration frameworks. · Understanding of microservices, REST APIs, containerization, and distributed systems. Requirements Video Systems, Media Processing & Streaming Architecture · Deep expertise in video capture, ingestion, encoding, transcoding, packaging, streaming, storage, and distribution. · Strong understanding of video codecs and standards: H.264, H.265/HEVC, AV1, MPEG-TS, MP4, RTSP, RTP, WebRTC, SRT, HLS, DASH. · Hands-on experience designing scalable video pipelines using FFmpeg, GStreamer, NVIDIA DeepStream, or equivalent frameworks. · Experience with edge-to-cloud video transportation architectures and low-latency streaming systems. · Knowledge of video quality optimization, bitrate adaptation, frame extraction, synchronization, and metadata management. Experience handling large-scale video workloads across distributed environments. Model Development, Training & Optimization · Experience building and training production-grade vision models on custom datasets. · Deep understanding of dataset design, annotation strategies, augmentation, transfer learning, and active learning. · Model optimization using TensorRT, ONNX Runtime, quantization, pruning, and GPU acceleration. · Experience deploying models across edge, cloud, and hybrid environments.