Engineering Manager, Inference Benchmarking — AI Perf

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 decisions on production inference by choosing GPUs, optimizing costs, reducing latency, improving efficiency, and scaling. AIPerf spans LLM, multimodal, diffusion, and computer vision inference. As Technical Lead Manager you will lead the engineering team within NVIDIA’s Dynamo organization, building and advancing the platform so AIPerf becomes the leading benchmarking tool for datacenter, local, and edge use cases. What You’ll Be Doing Driving 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). Taking ownership for the accuracy and statistical soundness of benchmark results that engineering groups throughout the industry depend on to inform production infrastructure decisions. Advising 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. Hiring, mentoring, and growing a team of senior engineers operating in a high‑velocity open‑source environment with active external contributors worldwide. What We Need To See Bachelor’s degree in Computer Science, Electrical Engineering, or related field, or equivalent experience. 8+ overall years of software engineering experience building performance‑critical infrastructure, ML tooling, or distributed systems. 3+ years of engineering leadership experience as a tech lead, 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 From The Crowd Extensive experience with vLLM, TRT‑LLM or SGLang internals along with 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. Salary and benefits: Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is $224,000 USD – $356,500 USD. Equity and benefits are also available. Why join NVIDIA? NVIDIA offers highly competitive salaries and a comprehensive benefits package. For more information, visit NVIDIA is committed to fostering an inclusive work environment and is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. #J-18808-Ljbffr NVIDIA