Senior Software Engineer, Data Center Workloads – Infrastructure

We are seeking a Senior Software Engineer to join our team in developing and executing software-driven characterization workflows on NVIDIA rack-scale systems. As part of our engineering organization, you will play a key hands-on role in running AI workloads across the full stack to analyze, characterize, and optimize power, performance, and drive behavior at system level.

Your primary responsibilities will include:

• Developing and running software tools, automation, and workloads to characterize power, performance, and drive behavior across NVIDIA rack-scale systems.
• Executing AI and system-level workloads to stress and evaluate behavior across the stack, including GPUs, CPUs, networking, storage, firmware, drivers, and system software.
• Building automated frameworks for data collection, telemetry, validation, correlation, and analysis of characterization results.
• Investigating system behavior under different workloads and operating conditions to identify bottlenecks, anomalies, and optimization opportunities.
• Working closely with hardware, firmware, driver, system software, performance, and validation teams to define characterization methodologies and debug cross-stack issues.
• Supporting bring-up, validation, and readiness activities for new rack-scale platforms and AI infrastructure.
• Creating clear documentation, test flows, and repeatable processes to improve coverage, efficiency, and reproducibility.

To be successful in this role, you will need:

• A B.Sc. or M.Sc. in Computer Science, Electrical Engineering, or a related field.
• 5+ years of software engineering experience, preferably in system software, infrastructure, validation, or performance-focused environments.
• Strong programming skills in Python and at least one system-level language such as C/C++.
• Experience developing automation and test infrastructure for complex hardware/software systems.
• Hands-on experience running, debugging, or optimizing AI, HPC, or large-scale system workloads.
• Good understanding of system-level architecture, including interactions across hardware, firmware, drivers, operating systems, and application layers.
• Experience working in Linux environments and with scripting, telemetry, logging, and data analysis tools.
• Strong debugging and problem-solving skills, with the ability to work across multiple engineering disciplines.
• Good communication skills and the ability to drive technical work in a fast-paced, cross-functional environment.