Be an early applicantLess than 25 applicants

Company

NVIDIA · 11 hours ago

Senior Distributed Acceleration Engineer, RAPIDS

North Carolina, United States

Full-time

Remote

Senior Level

$148K/yr - $276K/yr

5+ years exp

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Artificial Intelligence (AI)GPU

Growth Opportunities

H1B Sponsor Likely

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Responsibilities

Analyze, design, and implement optimized GPU algorithms for large-scale data analytics and machine learning

Architect and implement distributed GPU algorithms for dense multi-GPU single-node machines and more generally for multi-GPU multi-node environments

Expand and improve integration of RAPIDS into relevant high-level frameworks

Drive performance analysis, benchmarking, and troubleshooting of associated libraries.

Collaborate with a multi-functional team to understand requirements and implement or improve solutions

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

CUDAPythonDistributed SystemsAlgorithmsMachine LearningDeep LearningGPU ProgrammingPerformance AnalysisDebuggingHPCPyData StackNumPyPandasScikit-LearnDaskOpen-source ProjectsAnalytical Problem-SolvingDocumentation Skills

Required

MS or PhD in Computer Science, Computer Engineering or Electrical Engineering or related field in Deep Learning, Machine Learning, and Computer Vision or equivalent experience.

5+ years of proven experience in Computer Science, Artificial Intelligence, Applied Math, or related field

Strong analytical problem-solving skills, algorithms, and mathematics fundamentals.

Distributed System experience and development

Excellent software development skills: programming, debugging, performance analysis, and test design

Good communication and documentation habits.

Ability to work independently and manage your own development efforts.

Preferred

Experience developing distributed algorithms and running on distributed systems: HPC, Cloud, etc

Experience with debugging multi-language and multi-hardware systems

Experience with the PyData Stack: NumPy, Pandas, Scikit-Learn, Dask

Prior work on open-source projects

GPU programming knowledge is a plus, but if you don’t have it, we’re happy to teach you

Benefits

Equity

Benefits

Company

NVIDIA

Glassdoor

4.6

NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI.

Founded in 1993

Santa Clara, California, USA

10,001+ employees

https://www.nvidia.com

H1B Sponsorship

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