Engineering Manager, Inference Benchmarking — AI Perf

Details

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Today NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. NVIDIA’s open-source benchmarking platform, AIPerf, is the growing standard for assessing LLM serving performance across various inference frameworks. Hyperscalers, cloud providers, and enterprises use AIPerf to inform production inference decisions, including choosing GPUs, optimizing costs, reducing latency, improving efficiency, and scaling.

As Technical Lead Manager, you will lead the engineering team within NVIDIA’s Dynamo organization. Your responsibility is to build and advance the platform so AIPerf becomes the leading benchmarking tool for datacenter, local, and edge use cases across LLM, multimodal, diffusion, and computer vision inference. This position combines hands-on leadership with expertise in systems engineering, inference infrastructure, and open-source communities.

Responsibilities

• Drive the technical roadmap for AIPerf's core infrastructure: load generation, ZMQ-based microservices, GPU telemetry (DCGM/PyNVML), Prometheus metrics, statistical confidence intervals, and Kubernetes-native deployment.
• Take ownership for the accuracy and statistical soundness of benchmark results used industry-wide to inform production infrastructure decisions.
• Advise upstream engine integrations involving vLLM, TRT-LLM, and SGLang in partnership with NVIDIA's Dynamo and NIM teams to maintain AIPerf's relevance across emerging hardware, workload categories, and inference configurations.
• Hire, mentor, and grow a team of senior engineers operating in a high-velocity open-source environment with active external contributors worldwide.

Requirements

• Bachelor's degree in Computer Science, Electrical Engineering, or related field, or equivalent experience.
• 8+ years of overall software engineering experience building performance-critical infrastructure, ML tooling, or distributed systems.
• 3+ years of engineering leadership experience as a tech lead, technical lead manager (TLM), or engineering manager.
• Deep understanding of LLM inference mechanics — TTFT, ITL, KV caching, Prefill/Decode, speculative decoding — and the ability to reason about measurement correctness and reproducibility.
• Proven track record of collaborating across multi-functional groups and delivering production-quality output in high-velocity, high-external-visibility environments.

Ways to stand out

• Extensive experience with vLLM, TRT-LLM, or SGLang internals and contributions to their upstream projects.
• Experience building Kubernetes-native infrastructure including operators, Helm charts, and GPU observability tooling (DCGM, dcgm-exporter, PyNVML).
• Background in competitive benchmarking frameworks such as MLPerf or equivalent industry-standard evaluation systems.
• History leading or making meaningful contributions to active open-source projects with external communities.

Compensation and benefits

• Base salary range: 224,000 USD - 356,500 USD (final base determined by location, experience, and pay of employees in similar positions).
• You will also be eligible for equity and benefits. See www.nvidiabenefits.com for details.

Applications for this job will be accepted at least until June 1, 2026. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.