Responsibilities:
- Develop and optimize real-time computer vision applications for video analytics and edge AI solutions.
- Design and implement data pipelines to handle high-volume, real-time video streams.
- Build scalable, high-performance video processing pipelines with integration into cloud services or on-prem infrastructure.
- Collaborate with machine learning engineers to deploy deep learning models for object detection, segmentation, tracking, and classification on live video feeds.
- Ensure system performance, scalability, and robustness through optimization and efficient resource utilization.
- Participate in the full software development lifecycle, from requirements gathering to deployment and maintenance.
- Stay updated on the latest advancements in computer vision, machine learning, and deep learning technologies, incorporating them into the project roadmap.
Requirements:
- 3+ years of experience in computer vision or related fields.
- Expertise in NVIDIA DeepStream SDK for real-time video analytics and AI-based applications.
- Hands-on experience with Apache Kafka for building real-time data pipelines.
- Extensive experience in AWS
- Proficiency in OpenCV, GStreamer for image and video processing tasks.
- Strong experience with C++, Python, and libraries/frameworks such as
- TensorFlow, PyTorch, or TensorRT for deploying AI models.
- Understanding of video compression standards (H.264, H.265) and streaming protocols (RTSP, RTP, etc.).
- Familiarity with Docker and Kubernetes for deploying scalable microservices in cloud environments.
- Experience with Edge AI hardware like NVIDIA Jetson or similar platforms.
- Solid understanding of parallel computing and GPU acceleration techniques (CUDA).
- Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.
