Role at a glance
- Salary
- $152K – $287.5K/yr
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 3+ years of experience in C++ and Python programming.
- Education
- BS or equivalent experience in Computer Science, Electrical Engineering, or a related field.
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Role Summary
NVIDIA’s Deep Learning models performance engineering team builds and optimizes libraries and tools for designing, developing, and deploying efficient AI applications. The team works on open-source Deep Learning frameworks including PyTorch and JAX, Transformer Engine, NVIDIA GPUs and systems, and community benchmarks such as MLPerf.
What You'll Do
- Build and support Transformer Engine, the open-source library for accelerating the training of Large Language Models.
- Collaborate on systems research that improves Deep Learning model performance, such as training using extremely low precision and...
- Implement, benchmark, and optimize new Deep Learning models such as LLMs to scale efficiently on NVIDIA GPUs and systems.
- Build and contribute to NVIDIA submissions on community benchmarks such as MLPerf.
- Engage with the open-source community and support enterprise customers and partners by delivering the benefits of NVIDIA’s latest...
- Influence the design of new hardware generations and core platform software components for NVIDIA hardware and systems.
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View full postingQualifications
3+ years of experience in C++ and Python programming; strong background, experience, or coursework in parallel systems programming, preferably on GPUs; knowledge of Computer Architecture, Code Optimization, and/or Operating Systems; proven experience in developing large software projects; excellent verbal and written communication skills.
Required
- C++
- Python
- Parallel systems programming
- Computer Architecture
- Code Optimization
- Operating Systems
- Developing large software projects
- Excellent verbal and written communication skills
Preferred
- Experience in PyTorch, JAX, or any other DL framework.
- Experience with performance analysis, profiling, and code optimization techniques, especially with multi-GPU or multi-node systems.
- Knowledge of modern LLM architectures, attention mechanisms, and/or low-level DL libraries such as cuBLAS, cuDNN, and cuSOLVER.
- Experience in writing GPU kernels using any of - CUDA, OpenAI Triton, CuTeDSL, Pallas, or other similar libraries.
- Any past contributions to the open source community and/or experience working with multidisciplinary teams
Original job description
Content provided by the employer
Original job description
Content provided by the employer
Our Deep Learning models performance engineering team at NVIDIA is hiring software engineers at all experience levels to build and optimize the libraries and tools that enable Deep Learning Researchers and Engineers to design, develop, and deploy efficient AI applications. We are an ambitious and diverse team that builds optimizations directly into mainstream open source Deep Learning frameworks - PyTorch and JAX, which boost the performance at all levels of NVIDIA's AI stack. Our team has a wide collaborative footprint, working not only with multiple teams across NVIDIA but also with the broader open-source community to deliver SOTA Deep Learning performance on the best AI platform in the world!
What you will be doing:
Build and support Transformer Engine, the open-source library for accelerating the training of Large Language Models.
Collaborate on systems research that improves Deep Learning model performance, such as training using extremely low precision, parallelism methods, etc.
Implement, benchmark, and optimize new Deep Learning models such as LLMs straight out of groundbreaking research to scale efficiently on NVIDIA GPUs and systems.
Build and contribute to NVIDIA submissions on community benchmarks such as MLPerf.
Engage with the open-source community as well as support enterprise customers and partners by delivering the benefits of NVIDIA’s latest hardware and software innovations.
Influence the design of new hardware generations and core platform software components for NVIDIA hardware and systems.
What we need to see:
BS or equivalent experience in Computer Science, Electrical Engineering, or a related field.
3+ years of experience in C++ and Python programming.
Strong background, experience, or coursework in parallel systems programming, preferably on GPUs.
Knowledge of Computer Architecture, Code Optimization, and/or Operating Systems.
Proven experience in developing large software projects.
Excellent verbal and written communication skills.
Ways to stand out from the crowd:
Experience in PyTorch, JAX, or any other DL framework.
Experience with performance analysis, profiling, and code optimization techniques, especially with multi-GPU or multi-node systems.
Knowledge of modern LLM architectures, attention mechanisms, and/or low-level DL libraries such as cuBLAS, cuDNN, and cuSOLVER.
Experience in writing GPU kernels using any of - CUDA, OpenAI Triton, CuTeDSL, Pallas, or other similar libraries.
Any past contributions to the open source community and/or experience working with multidisciplinary teams also showcase readiness for the team's responsibilities.
You will also be eligible for equity and benefits.
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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.