NVIDIA Logo

NVIDIA

Senior Deep Learning Software Engineer, PyTorch - TensorRT Performance

Reposted Yesterday
Be an Early Applicant
In-Office or Remote
2 Locations
148K-288K Annually
Senior level
In-Office or Remote
2 Locations
148K-288K Annually
Senior level
The role involves optimizing performance of Torch inference with TensorRT, contributing to inference frameworks, and collaborating on deep learning solutions across diverse domains.
The summary above was generated by AI

We are now looking for a Senior Deep Learning Software Engineer, PyTorch-TensorRT Performance! NVIDIA is seeking an experienced Deep Learning Engineer passionate about analyzing and improving the performance of Torch inference with TensorRT! NVIDIA is rapidly growing our research and development for Deep Learning Inference and is seeking excellent Software Engineers at all levels of expertise to join our team. Companies around the world are using NVIDIA GPUs to power a revolution in deep learning, enabling breakthroughs in areas like Generative AI, Recommenders and Vision that have put DL into every software solution. Join the team that builds the software to enable the performance optimization, deployment and serving of these DL solutions. We specialize in developing GPU-accelerated Deep learning software like TensorRT, DL benchmarking software and performant solutions to deploy and serve these models.

Collaborate with the deep learning community to integrate TensorRT to PyTorch. Identify performance opportunities and optimize SoTA models across the spectrum of NVIDIA accelerators, from datacenter GPUs to edge SoCs. Implement graph compiler algorithms, frontend operators and code generators across the PyTorch, Torch-TensorRT, TensorRT software stack. Work and collaborate with a diverse set of teams involving workflow improvements, performance modeling, performance analysis, kernel development and inference software development.

What you'll be doing:

  • Analyze performance issues and identify performance optimization opportunities inside Torch-TensorRT/TensorRT.

  • Contribute features and code to NVIDIA/OSS inference frameworks including but not limited to Torch-TensorRT/TensorRT/PyTorch.

  • Work with cross-collaborative teams inside and outside of NVIDIA across generative AI, automotive, robotics, image understanding, and speech understanding to develop innovative inference solutions.

  • Scale performance of deep learning models across different architectures and types of NVIDIA accelerators.

What we need to see:

  • Bachelors, Masters, PhD, or equivalent experience in relevant fields (Computer Science, Computer Engineering, EECS, AI).

  • At least 4 years of relevant software development experience.

  • Excellent Python/C++ programming, software design and software engineering skills 

  • Experience with a DL framework like PyTorch, JAX, TensorFlow.

  • Experience with performance analysis and performance optimization

Ways to stand out from the crowd:

  • Architectural knowledge of GPU.

  • Prior experience with a AoT or JiT compiler in deep learning inference, e.g. TorchDynamo/TorchInductor.

  • Prior experience with performance modeling, profiling, debug, and code optimization of a DL/HPC/high-performance application.

  • GPU programming experience and proficiency in one of the GPU programming domain specific languages, e.g. CUDA/TileIR/CuTeDSL/cutlass/Triton.

GPU deep learning has provided the foundation for machines to learn, perceive, reason and solve problems posed using human language. The GPU started out as the engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA's GPU runs deep learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Two modes of the human brain, two modes of the GPU. This may explain why NVIDIA GPUs are used broadly for deep learning, and NVIDIA is increasingly known as “the AI computing company.” Come, join our DL Architecture team, where you can help build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field.

#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 148,000 USD - 235,750 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until December 15, 2025.NVIDIA is committed to fostering a diverse 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.

Top Skills

C++
Cuda
Python
PyTorch
Tensorrt

Similar Jobs

46 Minutes Ago
Easy Apply
Remote
USA
Easy Apply
152K-179K Annually
Junior
152K-179K Annually
Junior
Artificial Intelligence • Blockchain • Fintech • Financial Services • Cryptocurrency • NFT • Web3
You will upgrade blockchain nodes, automate processes to enhance service effectiveness, and identify investment areas for further automation.
Top Skills: AutomationBlockchainIntegration TestingService Oriented Architecture
46 Minutes Ago
Easy Apply
Remote
United States
Easy Apply
140K-160K Annually
Senior level
140K-160K Annually
Senior level
Healthtech • Software
The Lead Analytics Engineer will design and implement data models, standardize semantic layers, enhance data quality, and mentor other engineers while ensuring compliance with healthcare standards.
Top Skills: AWSDbtEmrGlueIcebergParquetS3SparkSQL
An Hour Ago
Remote or Hybrid
US
60K-108K Annually
Senior level
60K-108K Annually
Senior level
Artificial Intelligence • eCommerce • Information Technology • Internet of Things • Automation
This role involves selling Azure services, managing the full sales lifecycle, and cultivating client relationships while meeting sales goals.
Top Skills: AzureSalesforce

What you need to know about the Charlotte Tech Scene

Ranked among the hottest tech cities in 2024 by CompTIA, Charlotte is quickly cementing its place as a major U.S. tech hub. Home to more than 90,000 tech workers, the city’s ecosystem is primed for continued growth, fueled by billions in annual funding from heavyweights like Microsoft and RevTech Labs, which has created thousands of fintech jobs and made the city a go-to for tech pros looking for their next big opportunity.

Key Facts About Charlotte Tech

  • Number of Tech Workers: 90,859; 6.5% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Lowe’s, Bank of America, TIAA, Microsoft, Honeywell
  • Key Industries: Fintech, artificial intelligence, cybersecurity, cloud computing, e-commerce
  • Funding Landscape: $3.1 billion in venture capital funding in 2024 (CED)
  • Notable Investors: Microsoft, Google, Falfurrias Management Partners, RevTech Labs Foundation
  • Research Centers and Universities: University of North Carolina at Charlotte, Northeastern University, North Carolina Research Campus

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account