Engineering Manager, Inference Benchmarking — AI Perf

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.

About the Role

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.

Skills

Technical skills required for this role include:

• Expertise in systems engineering, inference infrastructure, and open-source communities.
• Hands-on leadership in building performance-critical infrastructure, ML tooling, or distributed systems.
• Understanding of LLM inference mechanics and the ability to reason about measurement correctness and reproducibility.
• Collaboration across multi-functional groups and delivery of production-quality output in high-velocity, high-external-visibility environments.

Benefits

As you plan your future, see what we can offer to you and your family. NVIDIA offers highly competitive salaries and a comprehensive benefits package. Applications for this job will be accepted at least until June 1, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) 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.