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The AI Engineer – Computer Vision & Video Analytics will design, optimize, and deploy production-grade computer vision systems supporting real-time video analytics and safety monitoring. This is a hands-on engineering role focused on building GPU-accelerated inference pipelines, integrating AI models into scalable applications, and improving the reliability, speed, and accuracy of video-processing solutions.
AI Engineer – Computer Vision & Video Analytics – Benefits:
- Health, dental, and vision insurance
- Paid time off and holidays
- 401(K) retirement savings plan options
- Opportunities for career advancement and professional growth
AI Engineer – Computer Vision & Video Analytics – Required Qualifications:
- 3+ years of professional experience developing and deploying production computer vision, machine learning, or deep learning applications.
- Strong Python programming skills with experience writing maintainable, production-quality code.
- Hands-on experience with OpenCV, PyTorch, and YOLO/Ultralytics or similar object-detection frameworks.
- Experience developing real-time or near-real-time video-processing and inference pipelines.
- Strong understanding of video analytics concepts, including frame processing, object detection, confidence thresholds, temporal filtering, and tracking.
- Hands-on experience optimizing GPU inference using technologies such as NVIDIA CUDA, TensorRT, and ONNX.
- Experience improving model and application performance through batching, quantization, profiling, latency reduction, and throughput optimization.
- Experience with asynchronous programming and high-performance I/O using tools such as asyncio and aiohttp.
- Experience building and integrating REST APIs, gRPC services, and other application interfaces.
- Experience deploying containerized applications using Docker in production environments.
- Strong troubleshooting and problem-solving skills, with the ability to diagnose model, application, infrastructure, and performance issues.
- Ability to collaborate effectively with AI, software engineering, product, and infrastructure teams.
- Strong ownership mentality with the ability to take solutions from initial design through production deployment and ongoing support.
AI Engineer – Computer Vision & Video Analytics – Preferred Skills:
- Experience building video analytics solutions for fleet management, transportation, telematics, industrial safety, IoT, robotics, or other real-time monitoring environments.
- Experience with Microsoft Azure services, including Azure Event Hubs and Azure Blob Storage.
- Experience using Azure Application Insights or similar application-monitoring and telemetry platforms.
- Familiarity with edge computing and deploying AI models to GPU-enabled or resource-constrained devices.
- Experience with model conversion, optimization, and deployment workflows using ONNX and TensorRT.
- Knowledge of MLOps practices, including model versioning, testing, monitoring, deployment automation, and performance tracking.
- Experience processing live camera feeds, recorded video, or high-volume streaming data.
- Understanding of production resiliency, fault tolerance, observability, and scalable distributed systems.
- Experience working in a fast-paced product environment with changing technical and business requirements.
JOB ID: 179217
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Olivier Ludunge