Phd Research Scientist Intern - jobs at Nvidia in Switzerland

What you’ll be doing:

• Enhance NVIDIA's GPU Networking offerings for accelerating AI workloads, such as NVIDIA Dynamo or NVIDIA NIXL.

• Research, Develop and evaluate new technologies, innovations relevant for scientific, Deep Learning, and data-intensive workloads.

• Create proof-of-concept to evaluate and drive such new technologies.

• Work on impactful projects involving state-of-the-art high-performance computing software and hardware.

• Designing and implementing services, runtime systems, and applications over SDK.

• Partner and collaborate with other forward-thinking team members and external researchers.

What we need to see:

• Pursuing a Ph.D. in Computer Science, Electrical or Computer Engineering from a leading university.

• Background in algorithm design, system programming, and computer architecture.

• Strong programming and software development skills.

• A teammate with a can-do attitude, high energy and excellent interpersonal skills.

• Ability and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment.

Ways to stand out from the crowd:

• Proven research track record.

• Experience and passion for system architecture,CPU/GPU/Memory/Storage/Networking.

• Stellar communication skills.

• Knowledge in Deep Learning frameworks and AI communication libraries (NCCL, UCX, MPI and equivalents).

November 29, 2025.

Please note: We will be reviewing applications on a rolling basis as they are submitted. We encourage you to apply early.

What you will be doing:

In this role, you will research and develop techniques to GPU-accelerate leading applications in high performance computing fields within scientific computing, computational engineering, and data science. You will be performing in-depth analysis and optimization to ensure the best possible performance on current and next-generation GPU architectures. This involves:

• Working directly with key application developers to understand the current and future problems they are solving, crafting and optimizing core parallel algorithms and data structures to provide the best solutions using GPUs, through both library development and direct contribution to the applications.

• Collaborating closely with diverse groups at NVIDIA such as the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and programming models, by investigating the impact on application performance and developer productivity.

What we need to see:

• Pursuing a MSc or preferably PhD degree in an engineering or computer science related discipline. While not a requirement, domain expertise in telecommunications, medical imaging, machine learning, deep learning, or natural sciences is helpful.

• Programming fluency in C/C++ and/or Fortran with a deep understanding of software design, programming techniques, and algorithms.

• Strong mathematical fundamentals, including linear algebra and numerical methods.

• Experience with parallel programming, ideally CUDA C/C++ and OpenACC.

• Strong communication and organization skills, with a logical approach to problem solving, good time management, and task prioritization skills.

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The successful candidate will demonstrate strong background in C++ and systems programming, ability to work independently and quickly learn new technologies, excellent communication skills, and motivation to solve sophisticated problems at the intersection of graphics, AI, and performance engineering. Knowledge in Vulkan, DirectX12, and machine learning frameworks is highly valuable.

What you'll be doing:

• Develop state-of-the-art tools for boosting performance of groundbreaking graphics applications

• Integrate AI/ML capabilities into performance analysis and optimization workflows

• Design and implement new features across large-scale, cross-platform C++ codebases

• Work with sophisticated build systems (Bazel) and modern development toolchains

• Contribute to debugging tools, profilers, and performance visualization systems

• Develop cross-platform solutions that work seamlessly on Windows and Linux

What we need to see:

• Pursuing Bachelor's Degree in Computer Science or equivalent field

• Excellent C++ development skills with deep understanding of systems programming

• Strong foundation in data structures, algorithms, and software architecture with a passion for clean, elegant, well-documented source code

• Ability to study sophisticated technologies with sparse guidance

• Experience with AI-assisted development tools (e.g., Cursor, GitHub Copilot, Claude, Codex)

• Comfort working in large, complex codebases

Ways to stand out from the crowd:

• Experience with modern graphics APIs (Vulkan, DirectX12, OpenGL)

• Familiarity with machine learning frameworks (PyTorch, TensorFlow, ONNX)

• Knowledge of GPU architecture and hardware performance characteristics

• Background in game performance optimization or profiling tools

• Experience developing debugging tools, compilers, or developer tooling

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NVIDIA has been defining computer graphics, PC gaming, and accelerated computing for more than 25 years. With an outstanding legacy of innovation, driven by phenomenal technology, and extraordinary people, NVIDIA is looking for a strong technical principal architect to join us in shaping the future. Principal Architects are innovators who can translate business needs into workable technology solutions. Their expertise is deep and broad. They are hands on, producing both detailed technical work and high-level architectural designs. As a principal architect in the Advanced Development team, you will explore technological challenges on accelerate networking and building AI data centers. Research new transport functions and semantics for optimizing AI workloads You will also be leading architectural and development efforts across numerous technological fields, related to the modern data center, such as distributed AI and deep learning solutions, data analytics, High Performance Computing (HPC), Software Defined Networking (SDN), virtualization, storage, and more.

What you’ll be doing:

• Enhance NVIDIA's future GPU Networking offerings for accelerating AI workloads.

• Lead vision, architecture and design of such technologies.

• Lead proof-of-concept development to evaluate and drive such technologies.

• Identify and evaluate new technologies, innovations and partner relationships for alignment with our technology roadmap and business value.

• Work with the community and maintainers to drive strategic technologies

What we need to see:

• Hold a M.Sc. or Ph.D. in Computer Science, Electrical or Computer Engineering from a leading university (or equivalent experience).

• 15+ years of industry experience (or equivalent) in systems architecture or related fields.

• Experienced in virtualization, networking and storage.

• Experienced in either Windows or Linux drivers, with a very good background of the other OS.

• Deep understanding of performance profiling and optimization techniques, together with defining and using HW offloads.

• A teammate with a can-do attitude, high energy and excellent interpersonal skills.

• Ability and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment.

Ways to stand out from the crowd:

• Shown research track record.

• Have experience and passion for system architecture,CPU/GPU/memory/storage/networking.

• Stellar communication skills.

• Knowledge in Deep Learning frameworks