NVIDIA

Full-stack Engineer

• Work with NVIDIA internal customers
• Design and build scalable software systems to manage NVIDIA’s cloud infrastructure.
• Building network and systems automation software for managing a multi-tenant cloud infrastructure
• Participate in open-source communities of software we leverage and build.
• Present to internal stakeholders and NVIDIA leadership on roadmaps, vision, & demos

Senior Software Engineer, Cloud Platform

Application Engineer

• Act as a technical specialist on NVIDIA switch ASICs and networking products, directly supporting OEM engineers and account managers.
• Establish deep technical engagement with OEM’s architects, system engineers, and developers.
• Provide on-site and remote support to debug hardware/software integration, including register-level analysis, counters, and traces.
• Assist OEM with ASIC SDK integration into their switch NOS (Network Operating System) stack and provide example code, documentation, and onboarding support.
• Investigate networking protocols and datacenter characteristics (L2/L3, OSPF, BGP, VXLAN/EVPN, RoCE, congestion control, load balancing).
• Support customer war-room scenarios by analyzing logs/traces, reproducing issues, and driving rapid resolution with internal teams.
• Deliver training, workshops, and technical collateral for OEM engineering teams.
• Provide guidance to NVIDIA product teams based on OEM's feature requirements and deployment models.

Field Application Engineer

• Provide onsite support for large datacenter deployments of NVIDIA AI solutions with our latest technology such as GB300 NVL72 and VR144.
• Solving complex hardware and deployment issues
• Be a technical specialist on GPU and networking products directly supporting sales account managers, working closely with the team to deliver outstanding AI datacenter solutions.
• Actively establish the technical relationship with our customer’s engineers, management, and architects at focus accounts.
• Identify customer architectures and key product requirements in the enterprise AI market.
• Provide technical and sales training to the direct sales team and channel partners.
• Establish strong relationships and communication channels with internal teams.

Senior Field Application Engineer

SDET

• Ensure manufacturing readiness for CPO products at NV manufacturing partners.
• Collaborate closely with RnD, PE and Operations to ensure robust manufacturing capabilities of CPO products and assure mass production is running smoothly.
• Yield analysis monitoring and drive continued improvement initiatives for NPI production lines.
• Maintain products’ quality by improving test stability, coverage, design and manufacturing process.
• Provide onsite engineering support: technical ownership and support for product or tests issues, test infrastructures and tests setups

Senior Product Test Engineer

Software Engineer

• Focus on one of three specialized tracks: TensorRT‑LLM – Inference Optimization (Python / PyTorch): Build and enhance high‑performance LLM inference pipelines. Analyze and optimize model execution, scalability, and memory use. Collaborate across framework and research teams to deliver efficient multi‑GPU model serving.
• TensorRT Compiler – Graph Optimization (C++): Work on the TensorRT compiler backend to improve graph transformations and code generation for NVIDIA GPUs. Develop compiler optimization passes, refine operator fusion and memory allocation, and collaborate with CUDA and hardware architecture teams.
• CuTe DSL & CUDA Kernels Development / Optimization (CUDA C++ / Python DSL): Design and tune GPU compute kernels and DSL implementations for core deep learning operations such as GEMM, MoE, Attention and Convolution. Profile, analyze and improve CUDA kernel performance to achieve maximum GPU efficiency.

AI Computing Software Development Intern

Solutions Engineer

• Primary responsibilities will include building AI/HPC infrastructure for new and existing customers.
• Support operational and reliability aspects of large-scale AI clusters, focusing on performance at scale, real-time monitoring, logging, and alerting.
• Engage in and improve the whole lifecycle of services—from inception and design through deployment, operation, and refinement.
• Maintain services once they are live by measuring and monitoring availability, latency, and overall system health.
• Provide feedback to internal teams such as opening bugs, documenting workarounds, and suggesting improvements.

Senior Solutions Architect – Infiniband and Networking Ethernet

• Lead and coordinate multi-functional teams to deliver customer infrastructure projects, ensuring clear assignment of responsibilities and effective collaboration.
• Build and maintain positive relationships with customers, OEMs, and internal collaborators, facilitating communication and alignment throughout the project lifecycle.
• Define project requirements and identify vital resources in partnership with relevant teams.
• Present technical solutions to customers and partners, validating achievements and resolving issues to ensure successful deployments.
• Analyze customer difficulties and deployment plans, conducting gap analysis to identify areas for improvement and drive resolution.
• Supervise installation, configuration, and validation of infrastructure, monitoring progress, resolving technical challenges, and ensuring timely delivery.
• Facilitate handover to support teams and provide ongoing post-deployment service, gathering feedback and driving continuous customer success.

Senior Solutions Architect – NVIS Customer Infrastructure Management

• Maintain large scale computational and AI infrastructure, focusing on monitoring, logging, workload orchestration (Kubernetes and Linux job schedulers).
• Perform end-to-end resolving across the stack, from bare metal and operating system, through the software stack, container platform, networking, and storage.
• Optimize scalable, production-ready Kubernetes-based container platforms coordinated with enterprise-grade networking and storage.
• Serve as a key technical resource, develop, refine, and document standard methodologies and operational guidelines to be shared with internal teams.
• Support Research & Development activities and engage in POCs/POVs to validate new features, architectures, and upgrade approaches.
• Create and deliver high-quality documentation, including runbooks, onboarding materials, and best-practice guides for customers and internal teams.
• Become the technical leader for assigned customer accounts, providing strategic guidance on DevOps and platform architecture and influencing long-term infrastructure and operations decisions.

Senior Solutions Architect, Cloud Infrastructure, DevOps

QA Automation Engineer

• You will be responsible for developing and integrating advanced CAD solutions and automation flows using AI and machine learning for VLSI design, verification, and implementation.
• Work closely with design, verification, and CAD teams to identify areas for improving VLSI workflows using advanced tools and methods.
• Research, prototype, and deploy AI-based algorithms.
• Develop and maintain scripts and automation infrastructure to enable seamless adoption of AI tools in the VLSI design process.
• Continuously review emerging AI technologies and methodologies to keep our CAD environment up-to-date.
• Provide technical support and training to engineering teams on AI-enabled CAD flows and best practices.

Senior VLSI CAD, AI Automation Engineer

Artificial Intelligence

• Develop AI performance tools for large scale AI systems providing real time insight into applications performance and system bottlenecks.
• Conduct in-depth hardware-software performance studies
• Define performance and efficiency evaluation methodologies
• Automate performance data analysis and visualization to convert profiling data into actionable optimizations
• Support deep learning software engineers and GPU architects in their performance analysis efforts
• Work with various teams at NVIDIA to incorporate and influence the latest technologies for GPU performance analysis

Senior AI DL Workload and Performance Analysis Engineer

• Provide onsite technical leadership for large-scale NVIDIA AI datacenter deployments, ensuring seamless integration and customer happiness.
• Lead technical deployments of NVIDIA AI systems, collaborate cross-functionally, support L11 factory integration.
• Troubleshoot and resolve complex hardware and deployment issues across GPU, networking, and storage technologies.
• Act as a technical expert supporting sales teams, driving adoption of NVIDIA solutions through close collaboration with customers and internal collaborators.
• Lead technical engagement with customer engineers, architects, and decision-makers to identify system architectures and key product requirements in the enterprise AI space.
• Support L11 factory integration activities by working with OEM partners to embed NVIDIA technologies into manufacturing workflows, accelerating deployment readiness and time-to-value.

Senior Field Application Engineer – AI Factory

Mechanical Engineer

• Mixed-Signal/Analog circuit design for High Speed Memory I/O Interfaces.
• Solve challenge of circuit designs in deep submicron CMOS FinFET processes.
• Take designs through productization and be involved in all stages of development.
• Work with multi-functional teams to optimize the designs.

Mixed Signal Design Engineer – RDSS Intern

• Develop a factory pipeline that will take an AI model in and produce a deployable service that is validated across Cloud, On-prem and Kubernetes environments.
• With the team, define and deliver rapid iterations on the group's technical strategies and roadmaps to deliver and improve the NIM factory.
• You will be designing interfaces, data modeling and schema design, and expanding observability over the factory pipeline and its compute infrastructure.
• Work with technical leaders designing and developing scalable and reliable factory components.
• You will collaborate with multiple AI model teams to understand their requirements to build an efficient infrastructure that improves every teams' productivity.
• Define metrics and drive improvements based on user feedback.
• You will mentor and collaborate throughout the team and with other teams to grow your colleagues and yourself.

Senior Software Engineer, Distributed Systems

• Develop, analyze and optimize factory infrastructure that will take an AI model in and produce a deployable service that is validated across Cloud, On-prem and Kubernetes environments.
• With the team, define and deliver rapid iterations on the group's technical strategies and roadmaps to deliver and improve the NIM factory.
• You will be developing harness, automating hardware acceptance, analyze benchmarks, data gathering and statistical analysis of systems health and performance analysis of NIMs
• Work with technical leaders designing and developing scalable and reliable factory acceptance and performance tuning of hardware platforms.
• You will collaborate with multiple AI model teams to understand their requirements to build an efficient infrastructure that improves every team's productivity.
• Define metrics and drive improvements based on user feedback.
• You will mentor and collaborate throughout the team and with other teams to grow your colleagues and yourself.

Senior Software Engineer – NIM Factory Infrastructure

Research Engineer

• Collaborate with research staff and GPU architects to design and implement computer architecture SW simulation tools that are used and trusted by both research and product groups.
• Help design infrastructure to support binary instrumentation, CUDA driver level extensions and runtimes.
• Craft shared infrastructure to accelerate exploration of new computer architecture ideas.
• Collaborate with research scientists to develop and evaluate new architecture concepts.
• Develop new tools and methods for computer architecture research.
• Transfer technology to product groups.