AI Infrastructure Engineer

The DGX Cloud Production Engineer at NVIDIA ensures our GPU cloud services deliver maximum reliability and uptime. They carefully prepare and plan changes to the system. They also manage capacity and performance. NVIDIA values diversity, curiosity, problem-solving, and openness. Our team includes people with varied backgrounds and perspectives. We encourage collaboration, big thinking, and risk-taking without blame. We promote self-direction on meaningful projects. We also provide support and mentorship to foster learning and growth.

What You’ll Be Doing:

• Design, build, deploy, and run internal tooling for large-scale AI training and inferencing platform built on top of cloud infrastructure.
• Conduct in-depth performance characterization and analysis on large multi-GPU and multi-node clusters.
• Engage in and improve the whole lifecycle of services-from inception and design through deployment, operation, and refinement.
• Support services before they become available through activities such as system design consulting, developing software tools, platforms, and frameworks, capacity management, and launch reviews.
• Maintain services once they are live by measuring and monitoring availability, latency, and overall system health.
• Scale systems sustainably through mechanisms like automation, and evolve systems by pushing for changes that improve reliability and velocity.
• Practice sustainable incident response and blameless postmortems.
• Be part of an on-call rotation to support production systems., Design, build, and maintain infrastructure software for large-scale AI training and inference. Improve efficiency, resiliency, availability, observability, and reliability across distributed AI systems. Develop APIs and tools, analyze failures from application through hardware levels, define reliability metrics, and support NVIDIA AI platforms. The role requires expertise in distributed systems, monitoring, debugging, software engineering practices, and AI infrastructure, with preferred experience in large clusters, RDMA stacks, telemetry, and deep learning frameworks., Lead the optimization and performance analysis of distributed training and inference workloads on NVIDIA GPU platforms, with responsibilities including debugging, benchmarking, and ensuring reliability of large-scale AI systems. Top Skills: C/C++Containerized EnvironmentsCudaInfinibandMegatronNcclNemoNsight SystemsNvlinkNvswitchPciePythonPyTorchRdmaRoceTensorrt-Llm General Motors

District Manager Parts and Service

18 Minutes Ago Remote or Hybrid United States Mid level Mid level Automotive * Big Data * Information Technology * Robotics * Software * Transportation * Manufacturing Leads aftersales performance across an assigned dealership district by driving revenue, customer retention, customer experience, and KPI achievement. Advises dealer leadership, executes GM customer care and aftersales initiatives, analyzes operational and performance data, develops business plans, improves service lane traffic, and resolves warranty and customer concerns. The role requires frequent territory travel, strong automotive service and parts knowledge, Excel proficiency, and the ability to legally operate a motor vehicle. Top Skills: Excel

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NVIDIA is looking for an outstanding, passionate, and dedicated Senior AI Infrastructure Engineer to join our DGX Cloud group. This engineering role will design, build and maintain large-scale production systems with high efficiency and availability using a combination of software and systems engineering practices. This role demands knowledge across different systems, networking, coding, databases, capacity management, continuous delivery and deployment, and open-source cloud-enabling technologies like Kubernetes and OpenStack., * BS degree in Computer Science or a related technical field involving coding (e.g., physics or mathematics), or equivalent experience.

• 5+ years of experience.
• A track record showing a good balance between initiating your own projects, convincing others to collaborate with you, and collaborating well on projects initiated by others.
• Background in infrastructure automation and distributed systems architecture focused on building tools to manage large-scale private or public cloud platforms in production.
• Experience working with one or more of the following languages: Python, Go, C/C++, Java.
• Comprehensive understanding in one or more of Linux, Networking, Storage, and Containers Technologies.
• Experience with Public Cloud and Infrastructure as a Code (IAAC) and Terraform.
• Distributed system experience.

Ways to Stand Out from the Crowd:

• Interest in crafting, analyzing, and fixing large-scale distributed systems.
• Systematic problem-solving approach, coupled with strong communication skills and a sense of ownership and drive.
• Capability to identify issues and improve code performance while automating routine tasks. Experience in operating or handling large private and public cloud systems based on Kubernetes or Slurm.

Design, build, deploy, and operate large-scale AI training and inference infrastructure. Responsibilities include distributed systems performance analysis, infrastructure automation, capacity management, service lifecycle ownership, monitoring, reliability improvement, incident response, and on-call support for multi-GPU and multi-node cloud platforms. The summary above was generated by AI, Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 152,000 USD - 241,500 USD for Level 3; and 184,000 USD - 287,500 USD for Level 4.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hard-working people in the world working for us. If you’re creative and self-motivated, we want to hear from you! NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services.