Full-Time

Senior Deep Learning Systems Software Engineer

AI Infrastructure

Posted on 12/7/2024

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI computing solutions

Automotive & Transportation
Enterprise Software
AI & Machine Learning
Gaming

Compensation Overview

$184k - $356.5kAnnually

+ Equity

Senior, Expert

Company Historically Provides H1B Sponsorship

Remote in USA

Remote position; preference for candidates based in California.

Category
Deep Learning
AI & Machine Learning
Software Engineering
Required Skills
Python
Pytorch
C/C++

You match the following NVIDIA's candidate preferences

Employers are more likely to interview you if you match these preferences:

Degree
Experience
Requirements
  • Masters in CS, EE or CSEE or equivalent experience
  • 8+ years of experience in application performance engineering
  • Experience using large scale multi node GPU infrastructure on premise or in CSPs
  • Background in deep learning model architectures and experience with Pytorch and large scale distributed training
  • Experience with application profiling tools such as NVIDIA NSight, Intel VTune etc.
  • Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture. Experience with NVIDIA's Infrastructure and software stacks.
  • Proven experience analyzing, modeling and tuning DL application performance.
  • Proficiency in Python and C/C++ for analyzing and optimizing application code
Responsibilities
  • Understand, analyze, profile, and optimize deep learning workloads on state-of-the-art hardware and software platforms.
  • Build tools to automate workload analysis, workload optimization, and other critical workflows.
  • Collaborate with cross-functional teams to analyze and optimize cloud application performance on diverse GPU architectures.
  • Identify bottlenecks and inefficiencies in application code and propose optimizations to enhance GPU utilization.
  • Drive end-to-end platform optimization from a hardware level to the application and service levels
  • Design and implement performance benchmarks and testing methodologies to evaluate application performance.
  • Provide guidance and recommendations on optimizing cloud-native applications for speed, scalability, and resource efficiency.
  • Share knowledge and best practices with domain expert teams as they transition applications to distributed environments.
Desired Qualifications
  • Strong fundamentals in algorithms and GPU programming experience (CUDA or OpenCL)
  • Understanding of NVIDIA's server and software ecosystem
  • Hands-on experience in performance optimization and benchmarking on large-scale distributed systems
  • Hands-on experience with NVIDIA GPUs, HPC storage, networking, and cloud computing.
  • In-depth understanding storage systems, Linux file systems, RDMA networking

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 stands out from competitors by offering a combination of hardware and software solutions, including cloud-based services like NVIDIA CloudXR and NGC, which enable scalable applications in AI and machine learning. The company's goal is to drive innovation in technology and provide advanced solutions that cater to a wide range of clients, from gamers to enterprises.

Company Size

10,001+

Company Stage

IPO

Total Funding

$19.5M

Headquarters

Santa Clara, California

Founded

1993

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

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

0%

2 year growth

-1%
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