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$184k–$357k/yr
Full-time
bachelor degree, postgraduate degree
Equity, Health Insurance
Posted 22d ago
Apply by Oct 1
~40 hrs/week
Responsibilities
You will architect and develop accelerated, distributed implementations of numerical algorithms and Python APIs for high-performance computing. Additionally, you will collaborate with partners to define technical roadmaps and optimize performance across various CPU and GPU architectures.
Requirements
Candidates must possess a degree in Computer Science, Applied Math, or Engineering with at least 6 years of relevant industry experience. Strong proficiency in Python, C++, and CUDA, along with deep knowledge of numerical computing libraries and parallel programming, is required.
Full job description
We are looking for an experienced software professional to contribute to design and development of accelerated and distributed implementations of Python APIs for numerical computing. In the last decade, Python has become the de-facto programming language for practitioners in AI, data science and HPC, through popular frameworks such as NumPy, SciPy, TensorFlow and PyTorch. These frameworks provide an efficient high-level programming interface, allowing their users to focus on their application while providing highly optimized implementations. NVIDIA has been at the forefront of providing GPU-accelerated implementations of the fundamental components of these frameworks.
Join our dynamic team to help develop and optimize GPU-accelerated and distributed implementations of Python numerical libraries, supporting Python-based frameworks in various ecosystems. This developer will be a crucial member of a team that is working to unlock the power of distributed GPU computing for domains such as scientific computing, data analytics, deep learning, and professional graphics, running on hardware ranging from supercomputers to the cloud!
What you will be doing:
Work closely with product management and internal or external partners, to understand use cases and requirements, and contribute to the technical roadmaps of libraries
Architect, prioritize, and develop accelerated and distributed implementations of numerical algorithms
Design future-proof Python APIs for accelerated numerical/scientific computing libraries
Analyze and improve the performance of developed APIs on various CPU and GPU architectures, especially as a part of customer-critical end-to-end workflows
Prototype integrations of developed APIs into targeted frameworks
Write effective, maintainable, and well-tested code for production use
Contribute to the development of runtime systems that underlay the foundation of multi-GPU computing at NVIDIA
What we need to see:
BS, MS or PhD degree in Computer Science, Applied Math, Electrical Engineering or related field (or equivalent experience)
6+ years of relevant industry experience or equivalent academic experience after BS
Excellent Python, C++ and CUDA programming skills
Strong understanding of fundamental numerical methods, dense and sparse array computing
Deep familiarity with Python numerical computing libraries (e.g. NumPy, SciPy), including accelerated implementations (e.g. CuPy, Jax.NumPy, NumS, cuNumeric)
Experience developing and publishing Python libraries, following standard methodologies for pythonic API design
Strong background with parallel programming and performance analysis
Ways to stand out from the crowd:
Experience using/contributing to Python libraries for data science (e.g. Pandas), machine learning (e.g. scikit-learn) and deep learning (e.g. TensorFlow, PyTorch)
Experience with low-level GPU performance optimization
Experience building, debugging, profiling and optimizing distributed applications, on supercomputers or the cloud
Background with tasking or asynchronous runtimes
Background on compiler optimization techniques, and domain-specific language design
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until August 25, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.
Offices: 2701 San Tomas Expressway, Santa Clara, CA 95050, US · No. 8, Ji Hu Rd., Taipei City, Taipei City 114, TW · Nanakramguda, Serilingampally Mandal, Plot # 6A&B, IT Park Layout, RR District, Hyderabad, Telangana 500046, IN · No. 127 Andheri Kurla Road, CNB Square, Mumbai, Village Chakala, Andheri East 400 093, IN · Survey No. 144/145, Samrat Ashok Path, Off Airport Road, Pune, Yerwada 411 006, IN
How much do Data & Analytics jobs in Santa Clara, CA pay?
Based on 862 listings with disclosed salaries, most data & analytics jobs in Santa Clara, CA pay between $131k–$334k per year. Individual offers vary with seniority, company size, and specialization.
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