Full-Time

Senior Python Compiler 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

$184k - $356.5kAnnually

+ Equity

Senior

Company Historically Provides H1B Sponsorship

Remote in USA

Candidates can work remotely from the listed cities in the US.

Category
Backend Engineering
FinTech Engineering
Software Engineering
Required Skills
Python
UI/UX Design
CUDA
NumPy
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
  • BS, MS or PhD degree in Computer Science, Electrical Engineering or related field (or equivalent experience)
  • 6+ years experience in compiler development and code optimization
  • Strong Python programming skills with track record of driving formulation or adoption of community standards
  • Fluent C, C++, and CUDA C++ programming skills
  • Experience designing, developing, tuning, navigating, and/or maintaining a large, complex, multi-language software stack (between C, C++, CUDA C++, and Python)
  • Good written communication, collaboration, and presentation skills with ability of working across team boundaries
  • Knowledge of Numba, NumPy, SciPy or a similar framework
Responsibilities
  • Architect, prioritize, and develop new features in CUDA Python
  • Analyze, identify, and improve the UX and performance of CUDA software in Python
  • Write effective, maintainable, and well-tested code for production use
  • Address unique challenges in developing and deploying Python GPU solutions
  • Engage with the Python community to develop and drive necessary protocols and standards for the NVIDIA CUDA platform
  • Evangelize CUDA programming in Python to encourage and empower adoption of the NVIDIA CUDA platform
Desired Qualifications
  • Deep understanding in the CUDA programming model and language features
  • Familiarity with Python ecosystem, language idioms, and pioneering solutions
  • Dexterity with compilers, static and dynamic analysis techniques, and dynamic code generation
  • Experience developing with the LLVM and MLIR compiler infrastructure
  • Experience in memory management of a multi-language project or development of domain specific libraries/languages for AI, Data Analytics or Scientific Computing

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 products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC). These products help developers, data scientists, and IT administrators perform complex tasks efficiently. NVIDIA differentiates itself from competitors by focusing on technological advancements and a diverse range of applications, including cloud-based services like NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. The company's goal is to drive innovation in computing and provide effective solutions for a wide array of clients, from gamers to enterprises.

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

-1%
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