Hiring: Engineering Manager, Deep Learning Inference Company: NVIDIA Location: Illinois, United States Job Posted Time: 2026-09-12 17:59:08 Employment Type: Full-time Target Skills & Keywords: Deep Learning Inference, GPU Programming, CUDA, Triton, CUTLASS, LLM Serving, Multimodal AI, Generative AI, Open-Source Frameworks, SGLang, vLLM, FlashInfer, TensorRT-LLM, PyTorch, Multi-GPU Communications, NIXL, NCCL, NVSHMEM, Performance Optimization, Distributed Inference, C/C++, Python, Agile, Technical Leadership Experience: - 6+ overall years of software development experience - 3+ years in technical leadership or engineering management - Proven record of deploying or optimizing deep learning models in production environments - Experience leading teams using Agile or collaborative software development practices Required Skills: - Strong background in C/C++ software design and development; proficiency in Python is a plus - Hands-on experience with GPU programming (CUDA, Triton, CUTLASS) and performance optimization - Ability to lead, mentor, and scale a high-performing engineering team focused on deep learning inference and GPU-accelerated software - Guide strategy, roadmap, and execution of OSS inference frameworks engineering - Partner with internal compiler, libraries, and research teams to deliver end-to-end optimized inference pipelines across NVIDIA accelerators - Oversee performance tuning, profiling, and optimization of large-scale models for LLM, multimodal, and generative AI applications - Guide engineers in adopting best practices for CUDA, Triton, CUTLASS, and multi-GPU communications (NIXL, NCCL, NVSHMEM) - Represent the team in roadmap and planning discussions, ensuring alignment with broader AI and software strategies - Foster a culture of technical excellence, open collaboration, and continuous innovation Qualifications: - MS, PhD, or equivalent experience in Computer Science, Electrical/Computer Engineering, or a related field - Significant open-source contributions to deep learning or inference frameworks such as PyTorch, vLLM, SGLang, Triton, or TensorRT-LLM (preferred) - Deep understanding of multi-GPU communications (NIXL, NCCL, NVSHMEM) and distributed inference architectures (preferred) - Expertise in performance modeling, profiling, and system-level optimization across CPU and GPU platforms (preferred) - Proven ability to mentor engineers, guide architectural decisions, and deliver complex projects with measurable impact (preferred) - Publications, patents, or talks on LLM serving, model optimization, or GPU performance engineering (preferred) Compensation: - Base salary range: 224,000 USD - 356,500 USD for Level 3 - Base salary range: 272,000 USD - 431,250 USD for Level 4 - Eligible for a comprehensive benefits package - Base salary determined based on location, experience, and pay of employees in similar positions Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don’t miss this opportunity to join a forward-thinking team!