HR POD - Hiring Talent GloballyIslamabad, Pakistan
5 days ago
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Job description
Requirements :
5+ years of experience in computer vision or related fields, with a proven track record of building and deploying algorithms for real-time applications (e.g., object detection, tracking, or segmentation).
Expert proficiency in Python and computer vision / ML frameworks (e.g., OpenCV, TensorFlow, PyTorch, YOLO, Detectron2).
Strong expertise in designing and optimizing real-time computer vision algorithms, with a focus on performance in resource-constrained environments.
Hands-on experience with ML Ops practices, including model deployment, containerization (Docker), orchestration (Kubernetes), and CI / CD pipeline development.
Deep understanding of machine learning and deep learning concepts, including CNNs, transformers, and optimization techniques.
Proficiency with version control systems (e.g., Git) and software engineering best practices.
Ability to lead complex projects, solve technical challenges, and collaborate effectively in a fast-paced, mission-driven environment.
Experience with cloud platforms (e.g., AWS, GCP, Azure) for scalable model deployment and data processing.
Willingness to participate in occasional on-call support for mission-critical systems.
Experience with real-time data processing, edge computing, or IoT systems, particularly for camera-based applications.
Familiarity with advanced computer vision techniques, such as multi-object tracking, 3D reconstruction, or low-light image processing.
Background in traffic safety systems, smart city technologies, or autonomous vehicle perception systems.
Expertise in managing large-scale image or video datasets, including data annotation pipelines.
Knowledge of hardware optimization for computer vision (e.g., NVIDIA Jetson, TensorRT, or embedded systems).
Contributions to open-source computer vision or ML Ops projects.
Responsibilities :
Architect and build high-performance computer vision algorithms for real-time detection of traffic violations (e.g., speeding, lane violations, stop sign running) and scene analysis, ensuring accuracy and low latency.
Develop and optimize end-to-end computer vision pipelines, from image preprocessing and model training to inference and deployment, using frameworks like OpenCV, TensorFlow, PyTorch, or ONNX.
Lead ML Ops efforts, including model deployment, versioning, monitoring, and performance optimization, using tools like Docker, Kubernetes, and CI / CD pipelines.
Collaborate with hardware engineers, backend developers, and data scientists to integrate computer vision models with IoT camera systems and cloud-based infrastructure.
Design and implement scalable data preprocessing and annotation workflows to ensure high-quality datasets for training robust vision models.
Mentor junior engineers, conduct code reviews, and enforce best practices for building maintainable, high-performance AI systems.
Monitor and troubleshoot production systems, participating in on-call rotations to ensure reliability and performance.
Contribute to system architecture decisions, balancing trade-offs between accuracy, speed, and resource constraints for real-time applications.
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Computer Vision Engineer • Islamabad, Pakistan
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