Senior Developer Technology Engineer - AI

2 Months ago • 8 Years + • Artificial Intelligence • $184,000 PA - $356,500 PA

Job Summary

Job Description

NVIDIA's Developer Technology team seeks a Senior Developer Technology Engineer - AI to research and develop GPU acceleration techniques for deep learning, machine learning, and other AI domains. Responsibilities include collaborating with experts, optimizing AI and HPC algorithms for CPU and GPU architectures, publishing findings, and influencing next-generation hardware/software design. The ideal candidate has 8+ years' experience, strong C/C++ skills, parallel programming expertise (CUDA, OpenACC, etc.), low-level performance optimization experience, and deep knowledge of CPU/GPU architecture. The role involves working at the forefront of AI technology breakthroughs, contributing directly to NVIDIA's success. This is a hybrid role with locations in Santa Clara, CA; Westford, MA; Austin, TX; Hillsboro, OR; and Durham, NC.
Must have:
  • Master's degree in CS/related field or equivalent experience
  • 8+ years relevant experience
  • C/C++ programming fluency
  • Parallel programming experience (CUDA, OpenMP, etc.)
  • Low-level performance optimization experience
  • CPU/GPU architecture expertise
Good to have:
  • Deep learning model parallelization expertise (NLP, CV, Recommender Systems)
  • Strong linear algebra understanding
Perks:
  • Equity
  • Benefits

Job Details

We’re currently seeking a Senior Developer Technology Engineer, Artificial Intelligence! Would you enjoy researching parallel algorithms to accelerate AI workloads on advanced computer architectures? Is it rewarding to investigate, find, and eliminate system bottlenecks to achieve the best possible performance of computer hardware? Could you be thrilled about an opportunity to partner with the Developer community, working at the forefront of technology breakthroughs that contribute to the success of an industry leader like NVIDIA? If so, the Developer Technology Team invites you to consider this role.

What you will be doing:

  • In this position, you will research and develop techniques to GPU accelerate workloads in deep learning, machine learning or other AI domains.

  • Work directly with other technical experts in their fields (industry and academia) to perform in-depth analysis and optimization of complex AI and HPC algorithms to ensure the best possible AI solutions on modern CPU and GPU architectures.

  • Publish and present discovered optimization techniques in developer blogs or relevant conferences to engage and educate the Developer community.

  • Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA.

What we need to see:

  • A Masters degree in Computer Science, Computer Engineering, or related computationally focused science degree (or additional equivalent experience).

  • You have 8+ years of relevant work experience or research.

  • Programming fluency in C/C++ with a deep understanding of algorithms and software development.

  • A background that includes parallel programming, e.g., CUDA, OpenACC, OpenMP, MPI, pthreads, etc.

  • Hands on experience doing low-level performance optimizations.

  • In-depth expertise with CPU and GPU architecture fundamentals.

  • Good communication and organization skills, with a logical approach to problem solving, and prioritization skills.

Ways to stand out from the crowd:

  • Expertise in parallelization and performance optimization of Deep Learning models arising from Natural Language Processing, Computer Vision, Recommender Systems, etc.

  • Excellent understanding of linear algebra.

What's DevTech? We are a global organization whose mission is to drive innovation we see in the market towards our products. As recognized specialists across many domains, our work makes valuable contributions in two important ways. Our solutions are at the cutting edge of technology, advancing NVIDIA’s leadership in accelerated computing. Our discoveries generate findings that benefit the Developer Community and provides guidance to our engineering teams to help make our products better. NVIDIA's success in the advancement and availability of Artificial Intelligence has created incredible growth across the Company, and our Developer Technology Engineering team has been steadily growing to meet the demands for our services.

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. Are you a creative and autonomous computer scientist with a genuine passion for parallel computing? If so, we want to hear from you. Come, join our AI Compute DevTech team and help build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field.

#LI-Hybrid

The base salary range is 184,000 USD - 356,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

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.

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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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