Full-Time

Applied Deep Learning Research Scientist

Numerics and Systems Performance

Confirmed live in the last 24 hours

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI computing solutions

Automotive & Transportation
Enterprise Software
AI & Machine Learning
Gaming

Compensation Overview

$160k - $431.3kAnnually

+ Equity

Mid, Senior

Santa Clara, CA, USA

NVIDIA accepts applications on an ongoing basis.

Category
Applied Machine Learning
Deep Learning
AI & Machine Learning
Required Skills
LLM
Python
Neural Networks
CUDA
C/C++
Requirements
  • MS or PhD degree in computer science, computer engineering or a related field. Equivalent experience in some of the areas listed below can substitute for an advanced degree.
  • At least 3+ years of relevant industry experience.
  • Familiarity with state of art neural network architectures, optimizers.
  • Experience with modern DL training frameworks and/or inference engines.
  • Fluency in Python, C++, or ideally both.
  • For numerics focused candidates: Experience with training neural networks (LLMs and multi-modal models are of particular interest), exploring model architectures and optimizers. Experience with quantization of neural networks, numerical analysis, number representations and computer arithmetic.
  • For the systems focused candidates: Experience with parallel programming and performance analysis, collective communications. Background in computer architecture. Experience with GPU computing and CUDA is not required but a big plus.
Responsibilities
  • Research of low-bit number representations and their effect on neural network inference and training accuracy. This includes requirements by the existing state of art neural networks, as well as co-design of future neural network architectures and optimizers.
  • Research various parallelization approaches for large neural networks (both training and inference), communication patterns and their performance limiters on large GPU systems, communication and computation overlap.
Desired Qualifications
  • Experience with GPU computing and CUDA is not required but a big plus.

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their main products are GPUs that enhance gaming experiences and support professional applications, along with AI and high-performance computing platforms tailored for developers and data scientists. NVIDIA differentiates itself from competitors by focusing on advanced technology and continuous innovation, ensuring their products meet the evolving needs of users. The company's goal is to lead in AI and HPC solutions, providing powerful tools and services that enable clients to achieve immersive experiences and drive advancements in their respective fields.

Company Stage

IPO

Total Funding

$19.5M

Headquarters

Santa Clara, California

Founded

1993

Growth & Insights
Headcount

6 month growth

0%

1 year growth

0%

2 year growth

0%
Simplify Jobs

Simplify's Take

What believers are saying

  • Acquisition of VinBrain enhances NVIDIA's AI-driven healthcare solutions.
  • Investment in Nebius Group boosts NVIDIA's AI infrastructure capabilities.
  • Partnership with Serve Robotics aligns with NVIDIA's focus on robotics and AI applications.

What critics are saying

  • Increased competition from AI startups like xAI challenges NVIDIA's market position.
  • Serve Robotics' rapid expansion may lead to financial strain if market growth lags.
  • Integration challenges from VinBrain acquisition may affect NVIDIA's operational efficiency.

What makes NVIDIA unique

  • NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.
  • The Omniverse platform enhances NVIDIA's capabilities in industrial AI and digital twins.
  • NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

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Benefits

Company Equity

401(k) Company Match