[Remote] Engineering Manager, Inference Benchmarking — AI Perf

Note: The job is a remote job and is open to candidates in USA. NVIDIA is a leading technology company known for its innovation in computer graphics and AI. They are seeking an Engineering Manager for their AIPerf benchmarking platform, responsible for leading the engineering team to advance the platform for LLM serving performance across various inference frameworks.

Responsibilities

• 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

Skills

• 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
• 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

Benefits

• Equity
• Benefits

Company Overview

Company H1B Sponsorship