NVIDIA

Engineer

• Lead design and development of NVIDIA’s Assembler and Disassembler for GPU compute.
• Work on binary analysis & instrumentation features like call graphs generation, program register usage and patching of GPU binaries
• Work with GPU architecture and debugger/profiler development teams to understand their requirements and deliver new features & product improvements.
• Collaborate closely with teams developing other related components to ensure compatibility, reliability, and high-quality code generation
• Working with customers/partners to collect feedback and drive innovative ideas and features to incorporate into the product

Senior GPU Compiler Development Engineer

Full-stack Engineer

• Lead and grow a team that delivers high-quality, scalable enterprise solutions
• Partner with engineering and platform team to design, implement, and validate LLM-based agents, tool calling, RAG patterns, and orchestration frameworks
• Build robust integrations and automation pipelines across ServiceNow
• Oversee multi-platform support (Windows, macOS, Linux, iOS, and Android)
• Lead incident response and resolution in accordance with processes
• Mentor the support team to deliver and operate services employees depend on
• Plan and manage team execution, including project prioritization and milestone tracking

IT Software Engineering Manager

• Lead complicated integrations combining new technologies, automating processes, and bringing up full software stacks
• Develop SDKs to be used for DPU SW development
• Create and maintain build system for complex SW products
• Develop tools using various NVIDIA proprietary and other cutting-edge technologies
• Collaborate with team members, Architects, design, QA teams, and verification

Senior Software Engineer – Infrastructure and Tools

Mechanical Engineer

• A role in physical design for NVIDIA GPU and Mobile chips
• Participate in various aspects of physical design, including full chip floorplanning, power/clock distribution, timing optimization, place & route, timing closure, power/signal integrity analysis, and physical verification
• Troubleshoot a wide variety of design and flow complicated issues, and apply proactive intervention
• Collaborate with RTL, DFT and Circuit designers to ensure high quality of design implementation

Physical Design Engineer

Software Engineer

• Research and develop techniques to GPU accelerate workloads in deep learning, machine learning or other AI domains
• Work directly with other technical experts in their fields (industry and academia) to perform in-depth analysis and optimization of complex AI and HPC algorithms to ensure optimal AI solutions on modern CPU and GPU architectures
• Publish and/or present discovered optimization techniques in developer blogs or relevant conferences to engage and educate the developer community
• Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA

Data Processing Developer Intern

• Join the Developer Tools team to work on software such as Nsight Systems.
• Work with a wide variety of hardware platforms, ranging from small embedded systems, to large multi-GPU and NUMA servers and clusters.
• Be the communicator between our Nsight Systems team, various chip and system design teams, and the metrics library team.
• Work with internal and external users to understand their software and performance goals, and use that knowledge to influence future chip design.
• Communicate across multiple teams to collect and understand the requirements.
• Understand how the underlying hardware and software works, and use that knowledge to deliver valuable features to the users.
• Participate in all phases of the software life cycle.
• Collaborate with team members across multiple time zones in a dynamic, high-energy work environment.
• Interact with internal and external users, help them get the maximum value out of our products, and deliver their feedback to the product team.

Software Engineer, CPU and SoC Profiling Tools

Backend Engineer

• Join the Developer Tools team to work on software such as Nsight Systems.
• Work with a wide variety of hardware platforms, ranging from small embedded systems, to large multi-GPU and NUMA servers and clusters.
• Participate in research and benchmarking activities to develop industry-leading technology solutions needed to collect large amounts of performance data with the smallest possible overhead.
• Communicate across multiple teams to collect and understand the requirements.
• Understand how the underlying hardware and software works, and use that knowledge to deliver valuable features to the users.
• Participate in all phases of the software life cycle.
• Work out performance benchmark and performance regression testing methodology.
• Drive research activities to productization in Nsight Systems and deliver value to our most advanced users.
• Collaborate with team members across multiple time zones in a dynamic, high-energy work environment.
• Interact with internal and external users, help them get the maximum value out of our products, and deliver their feedback to the product team.

Senior C++ Software Engineer, Developer Tools

Blockchain Engineer

• You will be part of a DGX Cloud team responsible for production systems that enable large scalable GPU clusters to be used for a variety of AI workloads.
• Designing and developing a massively distributed scalable platform which would be used to identify, diagnose and remediate non-performant GPU assets.
• Working with teams across NVIDIA to ensure production AI clusters run reliably and consistently with maximum performance.
• Evaluating system failures and improving services based on a well-defined incident management process.

Senior Software Engineer, Distributed Systems Engineer – DGX Cloud

Engineering Manager

• Look across the platform, from applications and frameworks to drivers and firmware — to identify software and hardware opportunities that accelerate storage performance.
• This includes developing new driver features, C++/CUDA libraries, and removing performance & power bottlenecks.
• Drive alignment of the storage acceleration roadmap across next-generation systems, frameworks, applications, and the broader storage ecosystem.
• Spokesperson for the global team, championing initiatives both internally and externally.
• Lead and coordinate the planning, scheduling, and carrying out of team projects and deliverables, ensuring successful completion and accountability for the global team.
• Contribute to the planning and execution of NVIDIA’s reference storage platforms.

Senior Manager, Software Development – GPU Accelerated Storage

• Architect new persistent data storage platforms that meet targeted AI/HPC workload requirements
• Own the solid state drive selection process, storage performance optimization and ensuring operational excellence in NVIDIA platforms using SSDs
• Lead system integration and optimizing storage performance and endurance for SSD based storage platforms for NVIDIA
• Track and influence storage-class memory industry roadmap to keep NVIDIA leading in technological advancements

Principal Software Development Engineer, Solid State Drives

Solutions Engineer

• Help architect and scale high-performance, distributed AI infrastructure on-prem or in the cloud built with the latest NVIDIA GPU supercomputers for new and existing customers.
• Act as a technical specialist on GPU and networking products, directly supporting sales account managers to secure design wins.
• Provide technical and onsite support to solve complex hardware and software problems, with a focus on deep learning inference.
• Collect, maintain, and analyze complex deployment data and logs to assess product health, identify technical challenges, and guide the customer to resolution of roadblocks.
• Actively establish and cultivate technical relationships with engineers and architects at key customer accounts.
• Identify customer architectures and key product requirements in the CSP/OEM AI market to efficiently implement NVIDIA's solutions.
• Develop technical solutions including hardware & software demos and example system designs.
• Offer technical and sales training to direct sales teams and channel partners.

Senior Solutions Architect – Data Center Infrastructure

• Working with NVIDIA Cloud Partners and OEMs in Public Sector on large data center GPU server and networking system deployments
• Guide customer discussions on network design, compute/storage, and support bring up of server/network/cluster deployments
• Become the primary technical driver for customers during the design, development, construction, integration, and production of GPU infrastructure and applications throughout the entire customer lifecycle
• Work as the customer's trusted advisor conducting regular technical customer meetings for product roadmap, cluster issue debugging, feature discussions and introduction to new technology solutions
• Partner with other SAs, Account Managers, Engineering, Product, and business leaders to align on strategies, assess technical needs, and secure business opportunities for NVIDIA
• Analyze and debug compute/network configuration and performance issues to deliver performant clusters
• Prepare and deliver technical content to customers including presentations, workshops, reference architectures, tutorials, publications
• Educate C-Suite-level decision-makers about the benefits of AI and high-performance computing
• Lead communication with customers and NVIDIA Management
• Provide constructive feedback to engineering and product regarding product requirements, customer experience, documentation, and tools
• Ability to travel ~20%

Senior Solution Architect, AI Infrastructure

Developer Relations

• Develop and maintain deep technical expertise in data processing and data science
• Serve as the trusted technical advisor, problem solver, and champion for the developer community passionate about data processing and data science
• Work with cross-functional partners to promote adoption of NVIDIA technologies like RAPIDS, CUDA-X Data Processing, and NVComp
• Accelerate critical workloads by demonstrating and integrating the NVIDIA software stack (tools, libraries, SDKs, NIMs, and blueprints) into partner products, platforms, and data pipelines, enabling comprehensive multi-cloud, hybrid, and on-prem solutions
• Guide partners through onboarding and integration by providing technical resources — such as sample code, guides, and demo pipelines — to accelerate data processing and data science adoption and foster co-innovation of next-generation solutions
• Map and monitor the developer ecosystem to identify growth opportunities, collaborating with engineering, product management, and marketing to inform roadmaps and optimize partner adoption strategies
• Engage partner technical leaders to drive best-practice integrations and resolve technical challenges, using regular syncs to track adoption, discover new workflows, identify blockers to partner adoption, and channel critical field insights back to NVIDIA product teams
• Closely engage with partners on building strategy and execution plans to grow data processing and data science capabilities into their solutions
• Drive early adoption of new products and support launch and go-to-market activities in collaboration with NVIDIA partner managers, solution architects, industry business development managers, and sales and marketing teams.

Senior Developer Relations Manager – Data Processing, Data Science

Cloud Engineer

• Work with NVIDIA internal customers
• Design and build scalable software systems to manage NVIDIA’s cloud infrastructure.
• Participate in responses to real-time operational events
• 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 – DGX Cloud Services and Software

• Analyze architectural requirements and perform trade-off analysis for implementation
• Deliver high performance, area and power efficient RTL Blocks
• Craft micro-architecture specification and implement high-quality RTL
• Deliver a fully verified, synthesis and timing clean block
• Collaborate with chip architects, verification engineers, formal verification engineers, and SoC integration engineers
• Identify potential IP solutions for specific use cases