Ai Agent Infrastructure Engineer Intern - Fall jobs at Nvidia in Germany

What you'll be doing:

• Crafting and building the next generation of AI-based developer tools for in-depth performance on GPUs.

• Apply your own knowledge and skills to build tools that are instantly used by CUDA developers all over the word.

• Gain exposure to a wide range of NVIDIA technologies, including GPU Hardware, CUDA compilers/drivers, and developer tools software.

What we need to see:

• Pursuing a Master's or higher degree in Computer Science or Computer Engineering.

• Strong programming skills with Python and C++.

• Completed coursework or possesses foundational knowledge in developing AI assistants.

Ways to stand out from the crowd:

• Familiarity with tool-calling integrations into AI pipelines and agentic systems.

• Skills in CUDA kernel programming, profiling, and targeting GPU hardware.

• Outstanding interpersonal skills and ability to work effectively as a great teammate.

• Highly motivated to apply our knowledge and eager to learn new skills in a fast-paced environment.

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’ll be doing:

• Design and implement novel algorithms that enhance the real-to-sim quality, using state-of-the-art reconstruction and generative techniques.

• Optimize the reconstruction training and rendering runtime towards speed of light.

• Contribute to a large codebase, combining Python and CUDA.

• Close collaboration with experienced engineering and research team members.

• Contribute to NVIDIA NuRec and other core NVIDIA products and libraries.

• Publish and present results in internal or external conferences and articles.

What we need to see:

• Pursuing MS or PhD in Computer Science, Computer Engineering, or a related area with a focus on computer graphics, computer vision, or machine learning.

• Hands-on technical knowledge on Neural Reconstruction, and Generative Models such as image and video diffusion models.

• Proven experience with Python and Pytorch as well as CUDA/Slang.

• Strong experience in robotic systems such as autonomous vehicles or humanoid robotics.

• Good software engineering fundamentals (source control, testing/validation, containerization).

• Strong communication and interpersonal skills are required along with the ability to work in a dynamic, product- and research-focused team.

Ways to stand out from the crowd:

• Strong coding architecture skills showed by contributing to large internal or open source projects.

• Experience with performance analysis and optimization, particularly for GPU-accelerated workloads is a plus.

• Experience with advanced CUDA development and optimization for graphics or vision applications.

• History of multi-disciplinary creativity and innovation (for instance, experience with hardware + software projects in graphics or robotics).

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:

• Develop and optimize scalable high-performance cryptographic primitives, algorithms, and building blocks on the latest GPU hardware architectures

• Emphasize robust long term software architectures and designs that effectively use many generations of hardware

• Work closely with internal(product management, engineering) and external partners to understand feature and performance requirements and deliver timely cuPQC releases.

What we need to see:

• PhD or MSc’s degree in Applied Mathematics, Computer Science, or related science or engineering field is preferred (or equivalent experience).

• 5+ years of experience designing and developing software for cryptography in low latency or high throughput environments

• Strong mathematical foundations.

• Advanced C++ skills, including modern design paradigms (e.g. template meta-programming, SFINAE, RAII, constexpr, etc).

• Strong collaboration, communication, and documentation habits.

Ways to stand out from the crowd:

• Experience developing libraries consumed by many users.

• Experience with CUDA C++, and GPU computing.

• Programming skills with contemporary automation setups for both building software (e.g. cmake) as well as testing (e.g. CI/CD, sanitizers).

• Strong understanding of mathematical foundations and algorithms used in cryptography, including but not limited to finite field arithmetic, lattice-based cryptography, and cryptographic hash functions.

What you'll be doing:

As a key member of our team, you will be contributing directly to the future of accelerated AI. Your role will be dynamic and deeply technical, placing you at the center of compiler innovation. You will lead the design, implementation, optimization, and maintenance of the core compiler technologies that accelerate massive deep learning workloads. This is a highly collaborative role where you'll work alongside the very engineers who built PyTorch for NVIDIA hardware, helping to pioneer new features and stay at the forefront of framework development. You'll dive deep into performance analysis, scrutinizing workloads running on thousands of GPUs to find optimization opportunities that will shape the future design of Thunder. Furthermore, you will be part of a vibrant ecosystem, working closely with leading compiler, library, and systems teams—including experts behind nvFuser, TVM, XLA, and CUDA—to translate the latest research into practical, high-impact solutions for the open-source community.

What we need to see:

We are looking for engineers who are excited about building powerful, user-centric tools and are comfortable working in a fast-paced, collaborative environment. Here are some of the expertise we would like to see:

• A Bachelor's, Master's, or Ph.D. in Computer Science or a related technical field (or equivalent experience).

• 8+ years of relevant work experience

• A strong command of Python and experience building complex, well-tested software systems.

• Hands-on experience with deep learning frameworks like PyTorch or JAX. You understand how models are built and where the performance challenges lie.

• A solid foundation in compiler concepts such as abstract syntax trees (ASTs), intermediate representations (e.g., SSA form), program analysis, and code generation.

• Excellent communication and collaboration skills, essential for working effectively in a distributed, open-source environment.

Ways to stand out from the crowd:

• Previous contributions to deep learning compiler projects (e.g., TVM, MLIR, IREE) or deep learning frameworks themselves.

• Deep expertise in the internals of PyTorch, particularly its compiler stack (TorchDynamo, TorchInductor).

• Experience with JAX-like functional transformations and their application in a compiler context.

• Familiarity with parallel programming, distributed systems, and writing high-performance CUDA code.

• A track record of impactful participation in open-source communities, such as through code contributions, design discussions, or mentorship.

What you will be doing:

• In this position, you will research and develop techniques to GPU accelerate workloads in deep learning, machine learning or other AI domains.

• Work directly with other technical experts in their fields (industry and academia) to perform in-depth analysis and optimization of complex AI and HPC algorithms to ensure optimal AI solutions on modern CPU and GPU architectures.

• Publish and/or present discovered optimization techniques in developer blogs or relevant conferences to engage and educate the developer community.

• Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA.

What we need to see:

• Currently pursuing a PhD or Master degree in Computer Science, Computer Engineering, or related computationally focused science degree.

• Programming fluency in C/C++ with a deep understanding of algorithms and software development.

• A background that includes parallel programming, e.g., CUDA, OpenACC, OpenMP, MPI, pthreads, etc.

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

Ways to stand out from the crowd:

• Expertise in parallelization and performance optimization of Deep Learning models arising from Natural Language Processing, Computer Vision, Recommender Systems, etc.

• Excellent understanding of linear algebra.

What you'll be doing:

• Design and implement new features to accelerate Network and Storage in the Kubernetes echo system

• Work closely with open source communities, participate in the relevant working groups

• Work with different teams across NVIDIA

What we need to see:

• BSc in Computer Science or equivalent program

• 6+ years of hands-on experience in software development, preferably with Golang

• Highly motivated with strong communication skills, the ability to work successfully with multi-functional teams, developers, and architects

• Coordinate effectively across organizational boundaries and geographies

• Strong self-initiative, independence, and flexibility to a new technology

• Deep understanding of network protocols, virtualization, and containers

• Strong background in designing, implementing, and debugging complex software

• Vast hands-on experience with Kubernetes or OpenStack echo systems

Ways to stand out from the crowd:

• Experience with working on open source projects

• Background with SR-IOV, DPDK, ROCE technologies

• Experience in developing Kubernetes Operators, CSI plugins and CNI Plugins

What you will be doing:

• Help build out and scale customer-facing APIs and systems for the DGX Cloud Kubernetes Platform

• Work with the Runtime and Cluster Architecture teams to provide a complete GPU-accelerated Kubernetes clusters to a wide variety of NVIDIA initiatives

• Be the voice of our customers to ensure they have a smooth experience to access the compute they need for the workloads they want

• Build platform services for other NVIDIA developers to bring their services to NVIDIA Kubernetes clusters

What we need to see:

• BS/MS in Computer Science or related field (or equivalent experience).

• 8+ years of relevant work experience.

• Experience in building foundational SaaS systems at scale, such as API design, user management, or authentication and authorization flows

• Proficiency in Go and building Go services at scale

• Experience with deploying and maintaining services atop Kubernetes

• Experience writing automation with Kubernetes (i.e. Controllers,CustomResourceDefinitions,etc.)

• Background with AWS or GCP and related technologies like S3, GCS, RDS, etc.

• Ability to solve issues across multiple layers: infrastructure, Kubernetes, application runtime

• Communicate effectively across a big organization, both within and outside the Kubernetes Platform organization

Ways to stand out from the crowd:

• Experience working on internal tools and services for large engineering organizations

• Experience working across multiple layers of cloud infrastructure such as CSP APIs, Terraform, Kubernetes, and custom controllers and automation atop

• Experience working deeply in and with the upstream Kubernetes apiserver code

• Background with user-facing APIs with a focus on customer and/or developer experience