Full-Time

Windows AI Software Engineer

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

$148k - $235.8kAnnually

+ Equity

Senior

Austin, TX, USA + 2 more

More locations: Santa Clara, CA, USA | Durham, NC, USA

Category
Backend Engineering
Game Engineering
Software Engineering
Required Skills
Data Structures & Algorithms
Pytorch
Machine Learning
C/C++
Data Analysis
Requirements
  • Bachelor's, Master's, or PhD in Computer Science, Software Engineering, Mathematics, or a related field (or equivalent experience)
  • 5+ years experience in a related software position
  • 2+ years of experience in AI inferencing pipelines and applications using ML/DL frameworks like PyTorch, ONNX Runtime, DirectML preferred
  • Excellent C++ programming and debugging skills with a strong understanding of data structures and algorithms
  • Strong analytical and problem-solving abilities, with the capacity to multitask effectively in a dynamic environment
  • Outstanding written and oral communication skills, enabling effective collaboration with management and engineering teams.
Responsibilities
  • Partnering with NVIDIA software, research, architecture, and product teams, aligning strategies and technical needs for fostering the ecosystem of AI on a Windows RTX PC.
  • Performing in-depth analysis and optimization of AI models, AI frameworks, data processing pipelines, and inference backends to ensure the best performance on current and next-generation GPU architectures.
  • Identifying and implementing compute and memory optimizations across the full AI inference stack on RTX Windows PC.
  • Developing model compression and fine-tuning techniques to reduce resource consumption and improve performance, enabling efficient deployment and better user experience.
  • Designing and implementing an optimized framework for running AI NPCs in gaming applications as part of the NVIDIA ACE Platform.
  • Collaborating with Microsoft to drive advancements in APIs, AI frameworks, and platforms for developing and deploying AI inferencing applications.
  • Ensuring the effective deployment of directed tests through collaboration with the automation team, thereby ensuring the robustness of automated testing.
Desired Qualifications
  • Understanding of modern techniques in Machine Learning, Deep Neural Networks, and Generative AI with relevant contributions to major open-source projects will be a plus.
  • Proficiency in lower-level system/GPU programming, CUDA, and developing high-performance systems.
  • Hands-on experience with building applications using graphics APIs like OpenGL, DirectX, Vulkan, etc.
  • Consistent track record of delivering end-to-end products with geographically distributed teams in multinational product companies.

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