Senior System Software Engineer Nccl - Partner Enablement jobs at Nvidia in Switzerland

What you will be doing:

• Investigate opportunities to improve communication performance by identifying bottlenecks in today's systems.

• Design and implement new communication technologies to accelerate AI and HPC workloads.

• Explore innovative solutions in HW and SW for our next generation platforms as part of co-design efforts involving GPU, Networking, and SW architects.

• Build proofs-of-concept, conduct experiments, and perform quantitive modeling to evaluate and drive new innovations.

• Use simulation to explore performance of large GPU clusters (think scales of 100s of 1000s of GPUs)

What we need to see:

• M.S./Ph.D. degree in CS/CE or equivalent experience.

• 5+ years of relevant experience.

• Excellent C/C++ programming and debugging skills.

• Experience with parallel programming models (MPI, SHMEM) and at least one communication runtime (MPI, NCCL, NVSHMEM, OpenSHMEM, UCX, UCC).

• Deep understanding of operating systems, computer and system architecture.

• Solid in fundamentals of network architecture, topology, algorithms, and communication scaling relevant to AI and HPC workloads.

• Strong experience with Linux.

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

Ways to stand out from the crowd:

• Expertise in related technology and passion for what you do. Experience with CUDA programming and NVIDIA GPUs. Knowledge of high-performance networks like InfiniBand, RoCE, NVLink, etc.

• Experience with Deep Learning Frameworks such PyTorch, TensorFlow, etc. Knowledge of deep learning parallelisms and mapping to the communication subsystem. Experience with HPC applications.

• Strong collaborative and interpersonal skills and a proven track record of effectively guiding and influencing within a dynamic and multi-functional environment.

What You Will Be Doing:

• Collaborate with lead robotics and simulation engineers to develop a new feature or integration prototype

• Test and validate the prototype in experiments using our robotics software stacks and/or robotic hardware

• Work in a large code base in a team of senior engineers

What We Need to See:

• You are pursuing an MS, or PhD in Computer Science, Robotics, Physics or related field

• Proficient analytical abilities, especially in analysis, linear algebra, numerical algorithms, and physics

• Advanced skills in Python and C++ programming, ideally with experience using AI-assisted development tools

• The ability to independently and efficiently debug code

• Solid foundation in software engineering best practices

• The capability for self-directed work and persistence when faced with complex problems

The Crowd:

• In-depth knowledge of physics engines like PhysX, MuJoCo, or Newton

• Hands-on experience with robotic manipulation and deep learning techniques for robotics

• Experience with NVIDIA’s robotics software stack, such as Isaac Sim and Isaac Lab

• Familiarity with NVIDIA Warp and CUDA programming

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

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).

• 8+ 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

What you’ll be doing:

• Develop algorithms, protocols, and network controllers

• Conduct simulations ranging from specific components to complete data center environments

• Design and implement services and runtime systems

• Define HW acceleration interfaces

• Evaluate and optimize application performance

• Partner and collaborate with industry leaders and external researchers

• Participate and speak at conferences and events

• Publish original research

What we need to see:

• MSc/PhD in Electrical Engineering, Computer Science/Engineering, or Post-doc

• 5+ years of proven experience

• Track record of independent research excellence

• Solid foundation in networking, operating systems, simulation, and systems

• Proficiency with firmware, system software, and embedded systems development to rapidly prototype

What you will be doing:

• Work with a geographically distributed partner organisation to understand, modify and improve CPU Compiler SW at NVIDIA.

• Contribute new features and optimisation techniques.

• Develop compiler SW that is optimised for performance.

• Be part of a team that is at the centre of AI, HPC and data centre technologies.

What we need to see:

• BS or MS degree in Computer Science, Computer Engineering, or related field or equivalent with minimum 3 years of work experience

• Experience with compiler development or a related academic or project.

• Knowledge of Language Front-Ends or Compiler optimisation techniques and code generation modules.

• Strong hands-on C++ programming skills

• Excellent verbal and written communications skills

Ways to stand out from the crowd:

• Familiarity with CPU architectures such as x86_64, PPC, RISC-V, Arm Architecture (AArch32, AArch64) or DSPs.

• Familiarity with industry standard compiler infrastructure such as LLVM and / or GNU Toolchain

• Knowledge of AI algorithms, scientific HPC applications and related code optimisations.

• A track record of contributing to open source compiler communities.

What you'll be doing:

You will play a crucial role in ensuring the success of the Omniverse on DGX Cloud platform by helping to build our deployment infrastructure processes, creating world-class SRE measurement and creating automation tools to improve efficiency of operations, and maintaining a high standard of perfection in service operability and reliability.

• Design, build, and implement scalable cloud-based systems for PaaS/IaaS.

• Work closely with other teams on new products orfeatures/improvementsof existing products.

• Develop, maintain and improve cloud deployment of our software.

• Participate in the triage & resolution of complex infra-related issues

• Collaborate with developers, QA and Product teams to establish, refine and streamline our software release process, software observability to ensure service operability, reliability, availability.

• Maintain services once live by measuring and monitoring availability, latency, and overall system health using metrics, logs, and traces

• Develop, maintain and improve automation tools that can help improve efficiency of SRE operations

• Practice balanced incident response and blameless postmortems

• Be part of an on-call rotation to support production systems

What we need to see:

• BS or MS in Computer Science or equivalent program from an accredited University/College.

• 8+ years of hands-on software engineering or equivalent experience.

• Demonstrate understanding of cloud design in the areas of virtualization and global infrastructure, distributed systems, and security.

• Expertise in Kubernetes (K8s) & KubeVirt and building RESTful web services.

• Understanding of building AI Agentic solutions preferably Nvidia open source AI solutions. Demonstrate working experiences in SRE principles like metrics emission for observability, monitoring, alerting using logs, traces and metrics

• Hands on experience working with Docker, Containers and Infrastructure as a Code like terraform deployment CI/CD.

• Exhibit knowledge in concepts of working with CSPs, for example: AWS (Fargate, EC2, IAM, ECR, EKS, Route53 etc...), Azure etc.

Ways to stand out from the crowd:

• Expertise in technologies such as Stack-storm, OpenStack, Redhat OpenShift, AI DBs like Milvus.

• A track record of solving complex problems with elegant solutions.

• Prior experience with Go & Python, React.

• Demonstrate delivery of complex projects in previous roles.

• Showcase ability in developing Frontend application with concepts of SSA, RBAC