Senior System Software Engineer – Dynamo Tools

NVIDIA • Austin, CA

1d

About The Position

We are seeking a Senior System Software Engineer to own and advance the AI-Perf analysis, NVIDIA’s flagship framework for benchmarking, experimentation, and analysis of LLMs, Generative AI, and deep learning inference workloads. In this role, you’ll combine systems research, distributed systems engineering, and applied AI, enabling reproducible performance evaluation, influencing internal platforms, and providing tooling that empowers researchers and engineers globally. What you’ll be doing: Lead the design, development, and roadmap of AI-Perf, defining benchmarking methodologies, performance metrics, and reproducible experimental workflows. Build scalable and high-performance features to measure latency, throughput, and efficiency across AI models and distributed systems. Partner with AI researchers, platform teams, and engineers to translate experimental challenges into robust, user-friendly performance tooling. Integrate AI-Perf with the Dynamo Inference Stack, other NVIDIA inference stacks, and open-source inference frameworks, delivering end-to-end performance insights for researchers and production users.

Requirements

• Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, or related field—or equivalent experience.
• 8+ years of experience in systems software, distributed performance engineering, or AI infrastructure research.
• Expert-level Python skills, including profiling, optimization, automation, and debugging of complex systems.
• Deep knowledge of distributed systems concepts, including scalability, concurrency, fault tolerance, and performance trade-offs.

Nice To Haves

• Experience designing or maintaining performance benchmarking frameworks or tooling for AI/ML systems.
• Hands-on experience with LLMs and deep learning frameworks such as PyTorch, TensorFlow, TensorRT, or ONNX Runtime.
• Contributions to open-source or research projects in AI performance, infrastructure, or distributed systems.
• Experience running large-scale inference experiments across cloud and on-prem environments (AWS, Azure, GCP, bare metal).

Responsibilities

• Lead the design, development, and roadmap of AI-Perf, defining benchmarking methodologies, performance metrics, and reproducible experimental workflows.
• Build scalable and high-performance features to measure latency, throughput, and efficiency across AI models and distributed systems.
• Partner with AI researchers, platform teams, and engineers to translate experimental challenges into robust, user-friendly performance tooling.
• Integrate AI-Perf with the Dynamo Inference Stack, other NVIDIA inference stacks, and open-source inference frameworks, delivering end-to-end performance insights for researchers and production users.

Benefits

• Impact at scale: Your work will define how AI performance is measured, optimized, and understood by engineers and researchers worldwide.
• Innovation and ownership: Lead a critical tool used by internal teams and external partners, shaping the AI benchmarking ecosystem.
• Collaborative research environment: Work closely with world-class AI researchers, engineers, and platform architects on cutting-edge inference challenges.
• Visibility and growth: Contribute to tooling that powers publications, benchmarks, and industry-leading AI performance insights.
• With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world's most desirable employers.
• We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our special engineering teams are growing fast.
• If you're a creative and autonomous engineer with a genuine passion for technology, we want to hear from you!
• Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
• You will also be eligible for equity and benefits .

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees