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Tier-1 brand, metro location, and mid-level seniority increase applicant competition despite niche AI/GPU specialization.
Strong GPU, computer-vision and embedded validation experience reduces cross-industry transferability.
Explicit 5+ years requirement plus mandatory Python, AI/ML, and GPU/container skills create strict shortlisting.
Develop and enhance Python-based test frameworks and CI/CD automation validating end-to-end Intelligent Video Analytics (IVA) and AI workflows across cloud, data center, workstation, and edge platforms.
Design and execute functional, integration, system, and end-to-end validation for NVIDIA Metropolis applications including Video Search & Summarization, covering multi-camera, multi-stream, multi-model, and simulation workflows.
Deploy and validate microservices AI architectures with Docker, Kubernetes, Helm; apply AI-powered tools throughout test lifecycle to accelerate test generation, analysis, coverage, and debugging.
B.Tech. or M.Tech. in Computer Science, Computer Engineering, IT, Electronics or related field, or equivalent experience.
At least 5 years of hands-on software test development or automation experience, preferably in AI/ML, computer vision, video analytics, embedded systems or GPU-accelerated applications.
Strong Python programming proficiency with experience building test frameworks and automation tools.
Proficient with Linux including shell scripting, system-level debugging, and process/resource analysis.
Experienced in AI/ML, computer vision, and video analytics domains with a strong understanding of AI inference pipelines and related technologies.
Comfortable working with containerized deployments, CI/CD tools, and distributed GPU environments.
Demonstrable experience applying AI-powered tools or agents to improve test automation efficiency, quality, and debugging capabilities.