Internship Electrical Engineer Nvidia Jobs in California

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology-and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

NVIDIA Warp brings Python productivity to high-performance simulation, scientific computing, and differentiable programming on CPUs and NVIDIA GPUs. Our team develops Warp for computational physics, AI, and optimization workflows. We are looking for a hands-on senior engineer to expand Warp's adoption across science and engineering.

Our goal is to make Warp a foundation for products and tools inside and outside NVIDIA. If you enjoy shaping the future of accelerated computing while making it easier to use, we would love to meet you.

What you'll be doing:

• Own and improve the end-to-end technical path for adopting Warp in computational applications, from native C++ and CUDA changes through production integration, validation, and long-term compatibility.

• Turn new CUDA features and programming models into supported Warp functionality that improves performance and portability across successive generations of NVIDIA accelerated-computing platforms and opens new application domains.

• Partner with internal engineering teams, including those behind ALCHEMI, BioNeMo, PhysicsNeMo, and Kit-CAE, to integrate Warp into their software, resolve technical barriers, and support production adoption.

• Select and integrate CUDA-X libraries and other computing technologies when they address recurring technical gaps, exposing them through consistent Python and native APIs.

• Design and implement Warp improvements that expand what researchers and developers can accomplish, including new APIs, programming abstractions, and reusable building blocks for simulation, optimization, and AI workloads.

What we need to see:

• A BS, MS, or PhD in Computational Science and Engineering, Computational Physics, Electrical Engineering, Computer Engineering, Mechanical Engineering, Aerospace Engineering, Computer Science with a focus on scientific computing, or a related computational engineering field, or equivalent experience.

• 8+ years of relevant software development experience in industry, academic research, or a combination of both.

• Significant professional or academic research experience building, debugging, profiling, and optimizing performance-critical CUDA C++ software for NVIDIA GPUs, including diagnosing performance and correctness issues involving parallel execution, GPU architecture, and memory behavior.

• Substantial work building, optimizing, and supporting computational software used in research or production, involving numerical methods, model validation, or scientific data pipelines.

Ways to stand out from the crowd:

• Ownership of framework integrations from prototype through production across multiple software projects.

• Hands-on experience designing and optimizing software for systems that combine CPUs, GPUs, memory, and high-speed interconnects, including data placement, communication, and architecture-aware performance tuning.

• Experience defining and evolving Python GPU programming systems across user-facing programming models, compilers, runtimes, and kernel libraries.

• Experience shipping and maintaining production-quality open-source software, including testing, CI/CD, packaging, compatibility, and release practices within a large distributed team.

• Hands-on experience developing, extending, or integrating commercial or open-source simulation software for multiphysics, CFD, semiconductor process or device simulation (TCAD), molecular dynamics, or related computational workloads. Examples include Ansys Fluent, Siemens Simcenter STAR-CCM+, COMSOL Multiphysics, OpenFOAM, LAMMPS, and GROMACS.

Widely considered to be one of the technology world's most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.