Engineering Manager, Deep Learning Inference
NVIDIA is hiring an Engineering Manager, Deep Learning Inference in Santa Clara, United States. It pays $184k-$288k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
- The posting mentions vLLM and PyTorch among its tools and skills.
- NVIDIA has 2,700+ other open roles on Level.
AI in this role
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 vLLM / SGLang, 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.
Drive the strategy, roadmap, and execution of NVIDIA’s inference frameworks engineering, focusing on Client AI.
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.
#LI-Hybrid
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:184,000 USD – 287,500 USD for Level 2; and 224,000 USD – 356,500 USD for Level 3.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 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.How we rate this
Engineering Manager, Deep Learning Inference at NVIDIA rates 97 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- What's a project where you used vLLM hands-on?
- Walk me through how you've used PyTorch in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: vLLM and PyTorch. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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