NVIDIA | NVIDIA

Engineering Manager, Deep Learning Inference

Full-time · US, DC, Remote
✓ Verified live on the employer's own system · added 3 days ago
Save search
Mid-level · 3+ yrs exp

Requirements

Education: Doctorate

Experience: 3+ years

Skills & tools

Team LeadershipMachine LearningManagementCommunicationsElectricalProgrammingC Plus PlusPython
Apply on company site ↗ See your fit → free

Full job description

- 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.

- 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.

- 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 184,000 USD - 287,500 USD for Level 2, and 224,000 USD - 356,500 USD for Level 3.

Applications for this job will be accepted at least until August 9, 2026.

More jobs at NVIDIA | NVIDIA

Similar jobs near US, DC, Remote

Tell me when more Engineering Manager, Deep Learning Inference jobs post near US, DC, Remote We re-check every listing against the employer’s own board — no résumé needed.

Search Engineering Manager, Deep Learning Inference jobs near US, DC, Remote → Browse all live jobs

This posting was published by NVIDIA | NVIDIA on their own careers system and is shown here with a direct link to apply there. Employers: for corrections or removal, contact jobs@veritahire.com.