Engineering Manager, Deep Learning Inference

Details

NVIDIA is seeking an exceptional manager of Deep Learning Inference Software to lead a world-class engineering team advancing AI model deployment. You will shape the software powering sophisticated AI systems, including large language models and multimodal generative AI, accelerated on NVIDIA GPUs.

The Deep Learning Inference team develops and optimizes open-source frameworks that make AI deployment scalable, efficient, and accessible, including SGLang, vLLM, and FlashInfer. This work enables developers worldwide to use NVIDIA accelerators for real-time inference at every scale, from datacenter clusters to edge devices.

Responsibilities

• Lead, mentor, and scale a high-performing engineering team focused on deep learning inference and GPU-accelerated software.
• Guide the strategy, roadmap, and execution of NVIDIA's open-source 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, including NIXL, NCCL, and NVSHMEM.
• Represent the team in roadmap and planning discussions, ensuring alignment with NVIDIA's broader AI and software strategies.
• Foster a culture of technical excellence, open collaboration, and continuous innovation.

Requirements

• Master's degree, PhD, or equivalent experience in Computer Science, Electrical or Computer Engineering, or a related field.
• At least 6 years of overall software development experience, including at least 3 years in technical leadership or engineering management.
• Strong background in C/C++ software design and development; proficiency in Python is a plus.
• Hands-on experience with GPU programming, including CUDA, Triton, and CUTLASS, and performance optimization.
• Proven record of deploying or optimizing deep learning models in production environments.
• Experience leading teams using Agile or collaborative software development practices.

Preferred Qualifications

• Significant open-source contributions to deep learning or inference frameworks such as PyTorch, vLLM, SGLang, Triton, or TensorRT-LLM.
• Deep understanding of multi-GPU communications, including NIXL, NCCL, and NVSHMEM, and distributed inference architectures.
• Expertise in performance modeling, profiling, and system-level optimization across CPU and GPU platforms.
• Proven ability to mentor engineers, guide architectural decisions, and deliver complex projects with measurable impact.
• Publications, patents, or talks on LLM serving, model optimization, or GPU performance engineering.

Benefits

NVIDIA offers highly competitive salaries, equity, and a comprehensive benefits package. The base salary is determined by location, experience, and the pay of employees in similar positions. Applications will be accepted at least until August 1, 2026.

NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer.