Engineering Manager, Deep Learning Inference

NVIDIA; Massachusetts; On-site; USD 224,000 - 431,000; Full time

Benefits offered by this job

Equity compensation

Comprehensive benefits

Job summary

NVIDIA is seeking an exceptional Manager, Deep Learning Inference Software, to lead a world-class engineering team advancing the state of AI model deployment. The role focuses on shaping software powering today’s AI systems — from large language models to multimodal generative AI — all accelerated on NVIDIA GPUs.

The Deep Learning Inference team develops and optimizes open-source frameworks such as SGLang, vLLM, and FlashInfer, enabling scalable, efficient AI deployment.

Qualifications

• MS/PhD or equivalent in CS/EE or related field.
• 6+ years in software development.
• 3+ years in technical leadership or engineering management.
• Strong background in C/C++ software design.
• Python proficiency a plus.
• Hands-on GPU programming (CUDA/Triton/CUTLASS).
• Experience deploying or optimizing DL models in production.
• Leadership with Agile or collaborative practices.

Responsibilities

• Lead and scale a high-performing engineering team focused on deep learning inference and GPU-accelerated software.
• Define strategy, roadmap, and execution for OSS inference frameworks engineering.
• Collaborate with internal compiler, libraries, and research teams to deliver end-to-end optimized inference pipelines.
• Oversee performance tuning and optimization of large-scale models for LLM, multimodal, and generative AI applications.
• Guide engineers in CUDA, Triton, CUTLASS and multi-GPU communications (NIXL, NCCL, NVSHMEM).
• Represent the team in roadmap discussions and align with broader NVIDIA strategies.
• Foster a culture of technical excellence and continuous innovation.

Skills

C/C++ design

Python

CUDA

Triton

CUTLASS

Agile

Production deployment

Education

MS/PhD or equivalent

Tools

SGLang

vLLM

FlashInfer

Job description

NVIDIA is seeking an exceptional Manager, Deep Learning Inference Software, to lead a world-class engineering team advancing the state of AI model deployment. You will shape the software powering today’s most sophisticated AI systems — from large language models to multimodal generative AI — all 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. Our work enables developers worldwide to harness NVIDIA accelerators for real-time inference at every scale, from datacenter clusters to edge devices.

What You’ll Be Doing

• 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 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 NVIDIA’s broader AI and software strategies.
• Foster a culture of technical excellence, open collaboration, and continuous innovation.

What We Need To See

• MS, PhD, or equivalent experience in Computer Science, Electrical/Computer Engineering, or a related field.
• 6+ overall years of software development experience, including 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 (CUDA, Triton, 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.

Ways To Stand Out From The Crowd

• 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 (NIXL, NCCL, 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.

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, our rapid growth means endless opportunities for career advancement.

If you’re a passionate technical leader ready to shape the future of AI inference frameworks — and build the software that powers the world’s most advanced models — we’d love to hear from you.

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 for Level 3, and 272,000 USD - 431,250 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 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.

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