Role at a glance
- Salary
- $152K – $287.5K/yr
- Location
- 2 Locations, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 5+ years of relevant work or research experience.
- Education
- A Master’s or PhD in Computer Science, Computer Engineering, Electrical and Computer Engineering, or a related field.
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Role Summary
This software engineering role focuses on accelerating AI, high-performance computing, and financial workloads on modern CPU and GPU architectures. The engineer will collaborate with technical experts and NVIDIA research, hardware, compiler, and tools teams to improve performance and influence future platforms, software, libraries, and programming models.
What You'll Do
- Design and develop techniques to accelerate high-performance workloads at the intersection of AI, math, and financial systems.
- Analyze, optimize, and scale complex AI and HPC workloads for modern CPU and GPU architectures.
- Profile and eliminate performance bottlenecks across algorithms, kernels, and system-level behavior.
- Publish and present work in conferences, talks, and blogs.
- Collaborate with NVIDIA research, hardware, compiler, and tools teams to influence future hardware architectures, system software,...
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View full postingQualifications
Strong hands-on experience with CUDA and parallel programming; deep understanding of CPU/GPU architecture fundamentals; fluency in C/C++; foundation in algorithms and software design; experience improving the performance of large-scale computational applications on GPUs; excellent understanding of linear algebra; strong communication and organizational skills.
Required
- Strong hands-on experience with CUDA and parallel programming
- Deep understanding of CPU/GPU architecture fundamentals and how they impact performance
- Fluency in C/C++
- A solid foundation in algorithms and software design
- Proven experience improving the performance of large-scale computational applications on GPUs
- Excellent understanding of linear algebra
- Strong communication and organizational skills
- Logical approach to problem-solving
Preferred
- Experience with inference optimization techniques and deploying optimized AI models in production
- Experience with TensorRT, TensorRT-LLM, and cuTile
- Experience parallelizing and optimizing machine learning methods such as decision trees, time-series models, and Monte Carlo simulations
Original job description
Content provided by the employer
Original job description
Content provided by the employer
We are looking for a software engineer with a strong background in parallel processing and GPU architecture to push the limits of performance at the intersection of AI, high-performance computing, and financial markets. In this role, you will dive deep into parallel algorithms, GPUs, and sophisticated systems, identifying and eliminating bottlenecks to unlock the full power of the world’s most advanced processing hardware.
You will collaborate with top experts across industry and academia, influence next-generation platforms, and share your insights with the global developer community. Do you enjoy solving hard technical problems, love performance tuning, and want your work to have a visible impact across an entire industry? If so, we'd love for you to consider this role.
What you will be doing:
Designing and developing groundbreaking techniques to accelerate high-performance workloads at the intersection of AI, math, and financial systems.
Working hands-on with leading technical experts to analyze, optimize, and scale complex AI and HPC workloads for modern CPU and GPU architectures.
Profiling and eliminating performance bottlenecks across the stack—from algorithms to kernels to system-level behavior.
Publishing and presenting your work in conferences, talks, and blogs to educate and inspire the broader developer community.
Influencing the design of future hardware architectures, system software, libraries, and programming models by collaborating closely with NVIDIA research, hardware, compiler, and tools teams.
What we need to see:
Strong hands-on experience with CUDA and parallel programming.
Deep understanding of CPU/GPU architecture fundamentals and how they impact performance.
A Master’s or PhD in Computer Science, Computer Engineering, Electrical and Computer Engineering, or a related field.
Fluency in C/C++ and a solid foundation in algorithms and software design.
5+ years of relevant work or research experience.
Proven experience improving the performance of large-scale computational applications on GPUs.
Excellent understanding of linear algebra.
Strong communication and organizational skills, with a logical approach to problem-solving and solid prioritization abilities.
Ways to stand out from the crowd:
Experience with inference optimization techniques and deploying optimized AI models in production.
Experience with TensorRT, TensorRT-LLM, and cuTile.
Experience parallelizing and optimizing machine learning methods such as decision trees, time-series models, and Monte Carlo simulations.
#LI-Hybrid
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.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.