16 hours ago
Pune, IndiaSenior
Responsibilities
- Develop Python-based test frameworks, validation tools, and CI/CD automation for NVIDIA Metropolis.
- Build functional, integration, system, and end-to-end tests for video AI applications and workflows.
- Validate video indexing, semantic search, multimodal understanding, retrieval, summarization, and Agentic AI workflows.
- Test distributed and microservices-based AI architectures, APIs, integrations, scalability, fault tolerance, and end-to-end behavior.
- Deploy and validate applications using Docker, Kubernetes, and Helm across distributed GPU and edge environments.
- Apply AI-powered tools and agents to test generation, code development, test analysis, coverage improvement, log analysis, regression triage, root-cause analysis, and code reviews.
- Benchmark AI pipelines for accuracy, latency, efficiency, resource utilization, scalability, and reliability.
- Partner with development, architecture, product, and release teams to resolve quality issues and communicate release readiness and quality metrics.
Requirements
- Bachelor’s or master’s degree in Computer Science, Computer Engineering, Information Technology, Electronics, or a related field, or comparable experience.
- At least 5 years of hands-on software test development or automation experience, preferably involving AI/ML, computer vision, video analytics, embedded systems, or GPU-accelerated applications.
- Strong Python programming skills and experience building test frameworks, automation infrastructure, utilities, and validation tools.
- Experience using AI-assisted development tools and AI-powered workflows for test development, code generation, test analysis, debugging, coverage improvement, or workflow optimization.
- Strong Linux skills, including shell scripting, system-level debugging, process and resource analysis, and command-line troubleshooting.
- Understanding of AI/ML and computer vision concepts including object detection, classification, tracking, video analytics, and inference pipelines.
- Experience with containerized deployments and CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or equivalent.
- Understanding of test planning, regression testing, defect lifecycle management, root-cause analysis, code and test coverage, and release validation.
- Preferred experience with NVIDIA Metropolis, DeepStream, Video Search & Summarization, TensorRT, CUDA, NGC, GPU inference technologies, real-time video streaming, Kubernetes, Helm, NVIDIA Jetson, RTX, data center GPUs, AI agents, multimodal AI, or Physical AI applications.
Benefits
- Competitive salary and a generous, comprehensive benefits package.
- Benefits information is provided at nvidiabenefits.com.
Tech Stack
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.