NVIDIA Logo

NVIDIA

Engineering Manager, Deep Learning Inference

Posted One Month Ago
Be an Early Applicant
In-Office or Remote
5 Locations
184K-357K Annually
Senior level
In-Office or Remote
5 Locations
184K-357K Annually
Senior level
Lead and scale an engineering team building GPU-accelerated deep learning inference frameworks. Drive strategy and roadmap, partner with compiler/libraries/research teams, oversee performance tuning and multi-GPU optimizations, mentor engineers, and deliver production-ready inference pipelines for LLM, multimodal, and generative AI across datacenter and edge platforms.
The summary above was generated by AI

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 the pay of employees in similar positions. The base salary range is 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 August 9, 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.

Similar Jobs

39 Minutes Ago
Remote or Hybrid
United States
Mid level
Mid level
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Manages Buick and GMC dealership relationships across the Milwaukee/Madison territory. Provides consultative coaching, analyzes sales and customer metrics, supports product and program launches, optimizes vehicle and parts inventory, and drives adoption of GM products and services. The role develops territory business plans, tracks dealership commitments, resolves concerns, monitors training and compliance, and travels frequently to assess operations and support program execution.
Top Skills: Data Visualization ToolsGm Consensus Allocation SystemGoogle WorkspaceReporting ToolsSpreadsheet ToolsVehicle Ordering System
40 Minutes Ago
Remote or Hybrid
United States
Junior
Junior
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Serves as the primary field representative for OnStar, connected services, loyalty programs, and subscription offerings across assigned dealerships. Builds dealer relationships, coaches sales and service teams, delivers training, analyzes performance data, develops action plans, supports product launches, troubleshoots technology platforms, and improves customer onboarding and loyalty. Requires up to 90% travel within the assigned territory and frequent dealership visits.
Top Skills: Gm Mobile AppGoogle Built-InGoogle WorkspaceMS OfficeOnstarOver-The-Air UpdatesSuper Cruise
44 Minutes Ago
Remote or Hybrid
United States
Senior level
Senior level
Fintech • Software
Lead and grow an inside sales team promoting a SaaS financial reporting platform. Responsibilities include recruiting and coaching representatives, developing sales and pipeline strategies, driving new business and account expansion, forecasting performance, supporting complex customer conversations, and presenting market insights to leadership. The role requires strong B2B enterprise software sales experience, sales methodology expertise, analytical forecasting skills, and the ability to build scalable revenue processes.
Top Skills: GongLinkedin Sales NavigatorOutreachSaaSSalesforce

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account