Analyze performance metrics and system telemetry to identify bottlenecks, regressions, and optimization opportunities.
Produce clear, data-driven competitive analyses and technical reports that help internal and external stakeholders position NVIDIA products effectively.
Develop and debug automation scripts for various benchmark performance and system monitoring data collection on Windows, Linux and MacOS.
Build and maintain scalable automation frameworks, AI agents, dashboards, and data pipelines that improve testing efficiency, coverage, and analytical robustness.
What we need to see
BS or MS degree
2+ years equivalent practical experience, in Computer Science, Electrical Engineering, Computer Engineering, or a related technical field.
Strong Python skills or proficiency in another scripting or programming language.
Hands-on interest in AI/LLM workloads, PC gaming, workstation applications, and content-creation workflows.
Solid understanding of PC and server architecture.
Experience working with large datasets, and strong analytical and troubleshooting skills.
Excellent communication, organizational, time management, and task prioritization skills.
Ways to stand out from the crowd
Familiarity with NVIDIA GPUs and NVIDIA Technologies.
Working knowledge of AI inference or training, finetuning concepts.
Experience building, benchmarking, or operating AI platforms and LLM inference stacks.
Experience developing AI agents or agentic workflows.
Knowledge of containerized and virtualized workflows, including Docker, Kubernetes, and virtual machines.