דרושים Senior Gpu Supercomputer Scheduler Engineer ב-אנבידיה ב-United States, Texas

What you will be doing:

• Drive strategic CSP partnerships, collaborate with keyhyperscaleCSPs to align project schedules, priorities, and technical roadmaps for next-generation data center platforms.

• Manage complex technical collaborations proactively, identifying and resolving critical issues before they impact customer deployments.

• Orchestrate internal stakeholder alignment ensuring CSP priorities are reflected across NVIDIA's engineering, product, and business.

• Create comprehensive customer program visibility through executive dashboards, status reports, and metrics tracking that provide real-time insights into CSP project health, risks, and milestone achievement.

• Lead large-scale deployment programs managing multi-rack, hyperscale infrastructure rollouts with complex technical dependencies, timeline coordination, and resource alignment across multiple internal teams.

What we need to see:

• Technical Expertise: Solid understanding of system software design, OS fundamentals, Linux kernel development, and hardware/software interfaces. Experience in GPU-based data center server architectures.

• Program Management: Proven ability to lead software development for rack-scale systems and data center servers, including complex hardware/software integration projects.

• Industry Collaboration: Experience partnering with hyperscalers to drive technical outcomes, manage dependencies, handle escalations, and communicate effectively at the executive level.

• Communication & Leadership: Exceptional ability to translate technical concepts for business stakeholders and align diverse teams toward common goals.

• BS or MS in Computer Engineering, Computer Science, or related field or equivalent experience.

• 8+ years of technical program management experience in HPC or data center server software development.

Ways to stand out from the crowd:

• Prior hands-on technology development experience in out-of-band manageability and observability solutions, system software/Linux kernel driver development, CUDA programming, or LLM/AI framework development.

What you’ll be doing:

• Working with tech giants to develop and demonstrate solutions based on NVIDIA’s groundbreaking software and hardware technologies.

• Partnering with Sales Account Managers and Developer Relations Managers to identify and secure business opportunities for NVIDIA products and solutions.

• Serving as the main technical point of contact for customers engaged in the development of intricate AI infrastructure, while also offering support in understanding performance aspects related to tasks like large scale LLM training and inference.

• Conducting regular technical customer meetings for project/product details, feature discussions, introductions to new technologies, performance advice, and debugging sessions.

• Collaborating with customers to build Proof of Concepts (PoCs) for solutions to address critical business needs and support cloud service integration for NVIDIA technology on hyperscalers.

• Analyzing and developing solutions for customer performance issues for both AI and systems performance.

What we need to see:

• BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience.

• 4+ years of engineering(performance/system/solution)experience.

• Hands-on experience building performance benchmarks for data center systems, including large scale AI training and inference.

• Understanding of systems architecture including AI accelerators and networking as it relates to the performance of an overall application.

• Effective engineering program management with the capability of balancing multiple tasks.

• Ability to communicate ideas clearly through documents, presentations, and in external customer-facing environments.

Ways to stand out from the crowd:

• Hands-on experience with Deep Learning frameworks (PyTorch, JAX, etc.), compilers (Triton, XLA, etc.), and NVIDIA libraries (TRTLLM, TensorRT, Nemo, NCCL, RAPIDS, etc.).

• Familiarity with deep learning architectures and the latest LLM developments.

• Background with NVIDIA hardware and software, performance tuning, and error diagnostics.

• Hands-on experience with GPU systems in general including but not limited to performance testing, performance tuning, and benchmarking.

• Experience deploying solutions in cloud environments including AWS, GCP, Azure, or OCI as well as knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes, data center deployments, etc. Command line proficiency.

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:

• 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:

• 100% kernel coding role

• Own end-to-end design and development, challenging existing paradigms and exploring innovative approaches for RDMA and high-speed TCP-based networks.

• Collaborate closely with cross-functional teams to define and implement robust networking algorithms, data management strategies, and distributed systems principles.

• Contribute to architecture, integration, and alignment with both on-prem and cloud-native platforms.

• Optimize system performance and reliability through in-depth analysis and low-level tuning.

• Stay up to date with the latest industry trends and contribute to open-source projects.

What we need to see:

• B.S. or M.S. degree in Computer Science or Electrical Engineering (or equivalent experience).

• 12+ years experience in development

• Proven professional experience in designing and developing distributed systems; advantage for experience in block storage and networking systems, advantage for cloud environments.

• Strong proficiency in C/C++ programming. Experienced with Linux Kernel internals including block subsystem, IO stack, memory management, and scheduling.

• Familiarity with storage protocols and standards, especially NVMe.

• Knowledge of networking fundamentals and experience in Linux-based networking environments.

• Familiarity with RDMA technologies, including Infiniband, RoCE, or iWARP, and experience with RDMA programming models, control and data paths.

• Knowledge of cloud computing concepts, including virtualization, scalability, and data management.

Ways To Stand Out From The Crowd:

• Excellent communication skills and a collaborative mindset.

• Perseverance and determination in debugging complex problems.

What you'll be doing:

• Building and maintaining infrastructure from first principles needed to deliver TensorRT LLM

• Maintain CI/CD pipelines to automate the build, test, and deployment process and build improvements on the bottlenecks. Managing tools and enabling automations for redundant manual workflows via Github Actions, Gitlab, Terraform, etc

• Enable performing scans and handling of security CVEs for infrastructure components

• Improve the modularity of our build systems using CMake

• Use AI to help build automated triaging workflows

• Extensive collaboration with cross-functional teams to integrate pipelines from deep learning frameworks and components is essential to ensuring seamless deployment and inference of deep learning models on our platform.

What we need to see:

• Masters degree or equivalent experience

• 3+ years of experience in Computer Science, computer architecture, or related field

• Ability to work in a fast-paced, agile team environment

• Excellent Bash, CI/CD, Python programming and software design skills, including debugging, performance analysis, and test design.

• Experience with CMake.

• Background with Security best practices for releasing libraries.

• Experience in administering, monitoring, and deploying systems and services on GitHub and cloud platforms. Support other technical teams in monitoring operating efficiencies of the platform, and responding as needs arise.

• Highly skilled in Kubernetes and Docker/containerd. Automation expert with hands-on skills in frameworks like Ansible & Terraform. Experience in AWS, Azure or GCP

Ways to stand out from the crowd:

• Experience contributing to a large open-source deep learning community - use of GitHub, bug tracking, branching and merging code, OSS licensing issues handling patches, etc.

• Experience in defining and leading the DevOps strategy (design patterns, reliability and scaling) for a team or organization.

• Experience driving efficiencies in software architecture, creating metrics, implementing infrastructure as code and other automation improvements.

• Deep understanding of test automation infrastructure, framework and test analysis.

• Excellent problem solving abilities spanning multiple software (storage systems, kernels and containers) as well as collaborating within an agile team environment to prioritize deep learning-specific features and capabilities within Triton Inference Server, employing advanced troubleshooting and debugging techniques to resolve complex technical issues.