Senior Computer Vision & Edge AI Support Engineer

Educational Requirements

Bachelor of Engineering, BTech, BCA, BSc, ME, MTech, MCA, MSc, MBA

Service Line

Data Analytics Unit

Responsibilities

• Provide production and application support for Computer Vision and Edge AI solutions.
• Monitor AI applications, inference services, edge devices, system health, logs, alerts, and performance metrics.
• Troubleshoot issues related to image-processing pipelines, video streams, AI models, cameras, edge devices, and system integrations.
• Perform root-cause analysis and drive timely resolution of production incidents.
• Support deployment and maintenance of Computer Vision models on edge platforms.
• Optimize AI inference for latency, throughput, memory utilization, and resource-constrained devices.
• Diagnose model, application, hardware-software integration, network, and environment-related issues.
• Work with Python, C++, OpenCV, PyTorch, TensorFlow, ONNX, or comparable Computer Vision technologies.
• Support object detection, image classification, segmentation, anomaly detection, and video-analytics solutions.
• Coordinate with AI/ML engineers, data scientists, platform teams, infrastructure teams, and business stakeholders.
• Document incidents, resolutions, known errors, operating procedures, and troubleshooting guides.
• Participate in incident, problem, change, release, and service-management activities.
• Identify opportunities to automate monitoring, support, deployment, and operational processes.

Technical and Professional Requirements

• 7-10 years of overall IT experience with significant experience in AI/ML, Computer Vision, or application support.
• Strong knowledge of Computer Vision, Edge AI, image processing, and video analytics.
• Hands-on experience with Python and/or C++.
• Experience with OpenCV and at least one ML framework such as PyTorch or TensorFlow.
• Understanding of object detection, classification, segmentation, and image-processing pipelines.
• Experience deploying or supporting AI models on edge or embedded platforms.
• Strong Linux troubleshooting, log analysis, debugging, and performance-analysis skills.
• Experience in production support, incident management, root-cause analysis, and problem management.
• Understanding of REST APIs, containerization, networking, and cloud or edge connectivity.
• Strong communication, analytical, and stakeholder-management skills.

Preferred Skills

• Technology->AI-Data science->Computer Vision