Senior Computer Vision Engineer

• C2-Scale Analytics Pipelines: Architect robust Python/C++ pipelines using frameworks like NVIDIA DeepStream, GStreamer, or OpenCV to execute concurrent video analytics across hundreds of live camera feeds.
• Event Telemetry & Alert Generation: Translate computer vision model outputs (bounding boxes, track IDs) into lightweight, structured JSON/Protobuf metadata payloads. Stream these alerts instantly to C2 event brokers using Kafka, MQTT, or gRPC
• Multi-Camera Tracking & Fusion: Develop algorithms for cross-camera re-identification (Re-ID) and spatial-temporal tracking, allowing the C2 system to map a subject’s trajectory across a physical site or facility layout.
• VMS & Enterprise Integration: Write custom plugins and middleware to interface directly with enterprise-grade Video Management Systems, network video recorders (NVRs), and unified access control physical layers.
• Performance Tuning for Command Centers: Profile, benchmark, and scale inference architectures using tools like TensorRT or ONNX Runtime to maintain strict sub-second end-to-end latency boundaries from camera sensor to C2 dashboard.
• Perimeter Security Sensors: Virtual/physical tripwire sensors, laser barriers, and IoT occupancy sensors.
• Hardware Integration Layers: Dry contact relays, Wiegand-to-IP converters, OSDP (Open Supervised Device Protocol), and Programmable Logic Controllers (PLCs).

Requirements:

• Experience: 5+ years of software engineering experience, with 3+ years specialized in deploying large-scale video analytics or telemetry pipelines integrated with operational monitoring systems (C2, VMS, or Smart City platforms).

• Programming Languages: Elite proficiency in Python and performance-critical C++.

• Frameworks & Infrastructure: Deep expertise in PyTorch/TensorFlow, NVIDIA DeepStream SDK, GStreamer, Docker, and distributed message queues (Kafka/RabbitMQ).

• Networking & Protocols: Thorough understanding of real-time streaming protocols (RTSP, WebRTC, SRT, HLS) and enterprise security transport configurations.