High Performance Ai Engineer jobs at Nvidia

We need a creative individual who will help transfer GPU gaming and compute products from design engineering to mass production. You will be exposed to various aspects of building and testing NVIDIA products, from GPUs to assembled boards. In addition, your responsibilities will include working with overseas manufacturing teams to increase yields, test coverage and capacity, and reduce production costs. If you are passionate about building the highest quality server products that will change the world, then we really want to hear from you.

What you'll be doing:

• Define, develop, implement, and support ATE test program solutions for the next generation of GPUs and AI server products.

• ATE test method code development and debugging

• Scripting and automation tools development and debugging

• Actively participate in cross function team including Product Development Engineering, DFT, and IC design to efficiently debug any product failures and implement optimal solutions

What we need to see:

• Completion of bachelor's degree or higher in Electrical Engineering/Computer Engineering (or equivalent experience).

• 5+ years of relevant work experiencein the semiconductor industry.

• Knowledge of silicon verification, testing and manufacturing

• Have knowledge in Advantest 93K ATE platform is essential

• Experienced with Linux, and programming languages such as C/C++/Java and/or Perl/Python

• Good communication skills and works well in a group environment and with cross functional teams that spans across continents

• Experience with SRAM testing and familiarity with 2.5D or MCM assembly

• Understanding of DFT insertion techniques including SCAN, ATPG, MBIST and IOBIST

• Knowledge of system level testing/validation is a plus

• Utilizing the AI in ATE testing is a plus and make you standout.

What you’ll be doing:

• Work closely with passionate engineers to design, develop, optimize, debug, unit test, document and maintain next-generation graphics and computing features for NVIDIA GPUs.

• We work on next-generation GPU hardware and software features through all phases of development, and you will get an opportunity to work across user and kernel stacks.

• Also work on customer issues and provide timely root cause of the problem and resolution.

• Collaborate with many internal teams (software, hardware, architecture, QA and OEM support), partners and customers to define new products and features, and resolve issues.

What we need to see:

• BS degree or higher or equivalent experience (computer science or related).

• 12+ years of industry experience.

• In depth understanding of Windows or Linux device drivers, PC architecture and ability to work close to the hardware.

• Proficient in C/C++ with strong software development, optimization and analytical skills.

• Strong debugging skills and extensive experience using gdb/kgdb/windbg to analyze complex pieces of software.

• Strong articulation skills for crafting and improving technical documents, and to engage globally distributed engineering team.

Ways to stand out from the crowd:

• Understanding of Virtualization concepts and system software for ESX, Hyper-V or KVM.

• Knowledge of DX/OGL graphics technologies, WDDM model.

• Familiarity with computer system architecture, microprocessor, and microcontroller fundamentals (caches, buses, memory controllers, DMA, etc.).

What you will be doing:

• Lead design and development of cutting-edge end-to-end reference system stack for 5G/6G baseband system.

• Developing and integrating modules like PDCP, RLC, MAC for 5G/6G air interface and L3 control plane.

• Work in lab environment to trouble-shoot and integrate complex software modules!

• Develop software, implementing new functions in C/C++/Python/CUDA in a multi-core environment.

• Support system integration, performance testing, system demonstration and lab trials for end-to-end system.

• Engage with customer field trials and technical teams.

• Be a technical bridge between engineering team and partners/customers engineering team!

• Help in implementing missing features to unblock progress at customers/partners.

What we need to see:

• 8+ years of LTE/5G network system experience focused on Radio Access Network.

• Bachelor’s or Master degree in electrical or computer science or related field (or equivalent experience).

• We are seeking candidates with end to end RAN integration knowledge.

• Experience in building RAN products like baseband system (eNB or gNB).

• Experience with cloud RAN, software defined networking, 5G macro and small cell deployments.

• Familiar with NFV, software virtualization, VM, containers and VNF’s.

• We seek experience in integrating with 5G NG and EPC cores.

• Experience in integrating with PHY layer.

• Direct experience in development, integration and testing of BBU functions like PHY, MAC, Scheduler, RLC, PDCP and RRC.

• Proficient in developing code using C/C++ on Linux based platform.

What You'll Be Doing:

• Working as a key member of our cloud solutions team, you will be the go-to technical expert on NVIDIA's products, helping our clients architect and optimize GPU solutions for AI services.

• Collaborating directly with engineering teams to secure design wins, address challenges, usher projects into production, and offer support through the project's lifecycle.

• Acting as a trusted advisor to our clients, while developing reference architectures and best practices for running Microsoft AI workloads on NVIDIA infrastructure.

What We Need To See:

• 4+ years of experience in cloud computing and/or large-scale AI systems.

• A BS in EE, CS, Math, or Physics, or equivalent experience.

• A proven understanding of cloud computing and large-scale computing systems.

• Proficiency in Python, C, or C++ and experience with AI frameworks like Pytorch or TensorFlow.

• Passion for machine learning and AI, and the drive to continually learn and apply new technologies.

• Excellent interpersonal skills, including the ability to explain complex technical topics to non-experts.

Ways To Stand Out From The Crowd:

• Recent projects or contributions (for example, on GitHub) related to large language models and transformer architectures.

• Knowledge of Azure cloud and AzureML services.

• Experience with CUDA programming and optimization.

• Familiarity with NVIDIA networking technologies such as Infiniband.

• Proficiency in Linux, Windows Subsystem for Linux, and Windows.

What you'll be doing:

• Enhance and maintain current-generation infrastructure and tools, addressing the needs of our customers for better platform capabilities, performance, and stability.

• Support partners in the development and deployment of their streaming experiences.

• Deploy various services and oversee their reliability and security.

• Write effective, clear and reliable architecture requirements and design specifications.

• Work closely and simultaneously with multiple NVIDIA expert teams around the world.

What we need to see:

• B.Sc./M.Sc. degree in Computer Science, Computer Engineering (or equivalent experience).

• 10+ years experience as a Full-Stack Software Developer.

• Broad knowledge and understanding of networking protocols and common network topologies, with a deep understanding of Cloud-based audio and video streaming.

• Hands-on cloud virtualization, networking, and orchestration experience.

• A combination of React, Javascript, Typescript, C/C++, Python or Go programming skills.

• Willingness to be full-stack across both frontend and backend is a must.

• Ability to understand customer needs and translate them into functional and user experience enhancements.

• Hands-on Linux development experience.

• Strong design, coding, analytical, debugging, and problem-solving skills.

• Excellent communication, documentation, and presentation skills.

Ways to stand out from a crowd:

• Background with data center technologies, network topologies and Cloud.

• Experience with Docker, Containers, Kubernetes components & subsystems.

• Experience with Proton and other virtualization technologies.

• Good understanding of operating systems and drivers.

• Experience developing and deploying deep-learning models: LLMs, text-to-speech, and more.

What you’ll be doing:

• Design, build, and run cloud infrastructure services in scope to meet our business goals performing integrations, migrations, bringups, updates, and decommissions as necessary.

• Participate in the definition of our internal facing service level objectives and error budgets as part of our overall observability strategy.

• Eliminate toil or automate it where the ROI of building and maintaining automation is worth it.

• Practice sustainable blameless incident prevention and incident response while being a member of an on-call rotation.

• Consult with and provide consultation for peer teams on systems design best practices.

• Participate in a supportive culture of values-driven introspection, communication, and self-organization

What we need to see:

• Proficiency in one or more of the following programming languages: Python or Go

• BS degree in Computer Science or a related technical field involving coding (e.g., physics or mathematics) or equivalent experience.

• 5+ years of relevant experience in infrastructure and fleet management engineering.

• Experience with infrastructure automation and distributed systems design developing tools for running large scale private or public cloud systems at scales requiring fully automated management and under active customer consumption in production.

• A track record demonstrating a mix of initiating your own projects, convincing others to collaborate with you, and collaborating well on projects initiated by others.

• In-depth knowledge in one or more of the following: Linux, Slurm, Kubernetes, Local and Distributed Storage, and Systems Networking.

Ways to stand out from the crowd:

• Demonstrating a systematic problem-solving approach, coupled with clear communication skills and a willingness to take ownership and get results such as experience driving a build / reuse / buy decision.

• Experience working with or developing bare metal as a service (BMaaS) associated systems. For example, vending BMaaS, or Slurm running on containers, or vending Kubernetes clusters. Experience working with or developing multi-cloud infrastructure services. Experience teaching reliability engineering (e.g. SRE) and/or other scale-oriented cloud systems practices to peers and/or other companies (e.g. CRE). Experience in running private or public cloud systems based on one or more of Kubernetes, OpenStack, Docker or Slurm.

• Experience with accelerated compute and communications technologies such BlueField Networking, Infiniband topologies, NVMesh, and/or the NVIDIA Collective Communication Library (NCCL).

• Experience working with a centralized security organization to prioritize and mitigate security risks. Prior experience in a ML/AI focused role or on a team matching specific keywords is welcome but not required.

What you'll be doing:

• Design, build and optimize agentic AI systems for the CUDA ecosystem.

• Co-design agentic system solutions with software, hardware and algorithm teams; influence and adopt new capabilities as they become available.

• Develop reproducible, high-fidelity evaluation frameworks covering performance, quality and developer productivity.

• Collaborate across the AI stack—from hardware throughcompilers/toolchains,kernels/libraries, frameworks, distributed training, andinference/serving—andwith model/agent teams.

What we need to see:

• Bachelor’s degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); MS or PhD preferred.

• 3 years+ industry or academia experience with AI systems development; exposure to building foundational models, agents or orchestration frameworks; hands-on experience with deep learning frameworks and modern inference stacks.

• Strong C/C++ and Python programming skills; solid software engineering fundamentals.

• Experience with GPU programming and performance optimization (CUDA or equivalent).

Ways To Stand Out From The Crowd:

• Strong experience in building/evaluating deep learning models, coding agents and developer tooling.

• Demonstrated ability to optimize and deploy high-performance models, including on resource-constrained platforms.

• Demonstrated ability in GPU performance optimizations, evidenced by benchmark wins or published results.

• Publications or open-source leadership in deep learning, multi-agent systems, reinforcement learning, or AI systems; contributions to widely used repos or standards.