Deep Learning Software Engineer, Performance Optimization

2 Months ago • 5 Years + • Artificial Intelligence

Job Summary

Job Description

NVIDIA seeks Deep Learning Software Engineers to develop and optimize deep learning solutions for consumer products. Responsibilities include analyzing and optimizing DNN AI algorithms, implementing production-quality software libraries for latency-critical applications on next-generation hardware, pushing performance and efficiency boundaries using techniques like model compression and quantization, collaborating with researchers and engineers on future NVIDIA chip architectures, and assisting customers in bringing AI-powered products to market. This role demands expertise in deep learning toolchains, neural network optimization, and accelerated hardware implementation.
Must have:
  • 5+ years experience in relevant fields
  • Proficiency in C++, Python
  • Deep learning toolchain knowledge
  • DNN optimization and implementation on accelerated hardware
  • Experience with CNN, LLM, ViT architectures
Good to have:
  • Experience with CUDA kernels or low-level libraries
  • Building distributed deep-learning infrastructure
  • Contributions to open-source projects
  • Publications at relevant conferences
  • Achievements in programming competitions

Job Details

We are looking for outstanding Deep Learning Software Engineers to develop and productize NVIDIA's deep learning solutions for use in real-life consumer products. The role gives opportunity to develop new deep learning architectures and tailor DNN-s for NVIDIA hardware platform. This role also involves building a close technical relationship with NVIDIA partners during product development and coordinate with internal architecture and software teams to develop the right solution for partners who rely on our platforms.

What you'll be doing:

  • Analyze, profile and optimize the latest DNN AI algorithms, and implement as production-quality software libraries for latency-critical use-cases on next-generation hardware.

  • Push the boundaries of the state of the art in DNN performance and efficiency, including model compression, quantization and architecture search techniques.

  • Collaborate with researchers and engineers across NVIDIA improving the architecture of future NVIDIA chips and ensure that they are ready to support the latest advances in AI.

  • Assist NVIDIA customers to bring ground-breaking products to life on the foundation of NVIDIA AI technology.

What we need to see:

  • University degree, or equivalent knowledge, in Computer Science, Electrical Engineering, Physics or Mathematics.

  • 5+ years of work experience in related fields, such as HPC, numeric computing, machine learning, AI with responsibilities for software optimization.

  • Proficiency in C++, Python, data structures, algorithms, computer architecture and operating system concepts.

  • Knowledge of deep-learning toolchains (PyTorch, TensorFlow, Keras, ONNX, TensorRT, numeric libraries, containers, etc.)

  • Experience with neural network training, pruning and quantization, deploying DNN inference in production systems.

  • Experience optimizing and implementing compute algorithms on accelerated hardware, such as SIMD instruction sets, GPU-s, FPGA or DNN ASIC.

  • Familiarity with CNN, LLM and ViT architectures, as well as the latest progress in the field.

  • Experience creating DNN models for solving production problems in any domain, including computer vision, speech recognition, natural language processing, optimization or generative AI.

Ways to stand out from the crowd:

  • Experience implementing DNN inference natively using C++, CUDA kernels or low level libraries, such as BLAS.

  • Experience building distributed deep-learning infrastructure, HPC, cloud programming.

  • Contribution to open-source projects, including personal projects published as open-source (please provide link to github repository).

  • Published paper at relevant conferences or in journals (e.g. NIPS, ICML, ICLR, CVPR, ICCV, ECCV, SIGGRAPH, etc.)

  • Achievements in programming or machine learning competitions, such as Kaggle, HackerRank, TopCoder, etc.

NVIDIA is leading the way in groundbreaking developments in artificial intelligence, high-performance computing and visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables outstanding creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for great engineers and scientists to help us accelerate the next wave of artificial intelligence.

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About The Company

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.


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