NVIDIA

Full-stack Engineer

• Contribute code to open-source parallel and distributed file systems and distributed object storage
• Upstream fixes and features and engage with upstream communities and maintainers
• Write and review production code as a hands-on storage software lead
• Read kernel, NFS, NVMe-oF, or SPDK source to diagnose bugs
• Make final technical calls on storage deliveries against measurable targets
• Triage, troubleshoot, and root-cause complex storage issues across very large GPU clusters
• Investigate I/O and metadata performance, data corruption, and recovery
• Validate storage architecture, capabilities, performance, and durability
• Run scale tests, benchmarks, and recovery drills
• Qualify new builds against measurable performance and durability targets
• Define and recommend configuration, tuning, and operational best practices for high-performance file systems on GPU infrastructure
• Help operators and internal customers apply storage guidelines
• Collaborate with training, inference, accelerated-computing, SRE, operations, networking, and security teams
• Collaborate with cloud providers, neocloud operators, and storage vendors on common architecture
• Use modern AI coding and agentic tools to accelerate building, debugging, validation, and operations

Senior Storage Software Engineer – DGX Cloud

Solutions Engineer

• Join NVIDIA's Solution Engineering team focused on Mellanox Networking, DGX Platforms, Container Orchestrators, Deep Learning containers, and enterprise system software
• Spend approximately 50% of time helping customers with complex problems and 50% on R&D-related work
• Take ownership of customer issues concerning InfiniBand/NVLink switch deployments from inception to resolution
• Develop features and tools supporting Enterprise Service offerings, including Networking products
• Work with NVIDIA Enterprise customers and internal users to improve availability, reliability, and overall experience with NVIDIA Networking products
• Apply independent analysis, communication, and problem-solving to customer experience
• Collaborate with engineering to document, recreate, and solve issues

Senior System Engineer, Solution Engineering

Business Operations

• Drive automation across the procurement lifecycle by building on existing automations and identifying new opportunities to improve efficiency within internal operations and supplier interactions
• Improve and develop reporting mechanisms for procurement activities, including order status by project, equipment lead times, contract statuses (SOW, PSA, MSA), and data center capacity lease activities
• Apply analytical skills to identify trends and patterns, build models, and present findings and recommendations
• Expose business exceptions and unfavorable outcomes through data analysis and develop mitigation strategies
• Foster strong business partnerships across a highly matrixed environment
• Collaborate with Finance, Procurement, Engineering, Vendors, Legal, Business Analysts, Business Owners, and Service Owners

Technical Program Manager – Business Operations Procurement Management

• Drive the implementation, deployment, and optimization of NVIDIA Inference Microservices (NIM) solutions for enterprise and industry AI workloads
• Package and serve open-source, NVIDIA, and customer-proprietary models through NIM with standardized, containerized APIs for on-premises, cloud, and hybrid environments
• Optimize high-volume inference and rollout workloads for LLMs and VLMs
• Evaluate and tune NIM models
• Deliver technical projects, demos, and client support tasks as directed by Solution Architecture Leadership
• Provide technical support and guidance to customers, facilitating adoption and implementation of NVIDIA technologies and products
• Collaborate with cross-functional teams to enhance and expand the AI solutions portfolio

NIM Solution Architect

• Work with ISVs and end customers to understand their software architecture, technical requirements, and business workflows, then guide them toward the best NVIDIA-based solution
• Help ISVs integrate the right NVIDIA SDKs, libraries, and platform capabilities into their existing applications to accelerate performance, enrich functionality, and improve customer outcomes
• Support technical discovery, proof-of-concept development, solution validation, and production adoption for industry software platforms
• Collaborate with headquarters engineering, product, and partner teams in English to resolve technical issues, influence roadmap alignment, and ensure strong execution for strategic ISV engagements
• Analyze workflow bottlenecks, application behavior, and deployment trade-offs, then recommend practical architectures that improve performance, scalability, and usability for customers

Senior Solution Architect – ISV

Manager

• Build and lead a world-class Data Center Operations team covering hardware operations support, network operations support, and supporting infrastructure at scale
• Establish NVIDIA’s strategic approach to global Data Center growth and operations
• Anticipate growth and scaling issues and implement solutions
• Work with cross-organizational business partners to establish a Data Center Lab support model
• Develop metrics, dashboards, KPIs, and reporting tools to measure organizational performance and drive continuous optimization
• Establish strong relationships with internal and external partners and foster a transparent, collaborative business unit
• Facilitate key meetings and communications to align executive and senior leadership on Data Center status, growth roadmap, and cross-functional initiatives
• Identify, track, and prioritize key risks and develop mitigation strategies
• Establish processes and workflows to transition from reactive responses to proactive, planned services

Regional Data Center Manager

• Contribute to verifying, debugging, developing, and designing simulation platforms for next-generation NVIDIA data center systems
• Improve simulation performance, fix bugs across the user and kernel stack, and automate execution flow
• Collaborate globally with hardware modelling, kernel, and platform driver teams to bring the full software stack up on the Data Center Platform Simulator

Software Engineer – Simulation and Virtualization, RDSS Intern

Developer Relations

• Work with China’s industrial and research community to integrate NVIDIA’s GPU-accelerated computing portfolio
• Serve as a technical business development and accelerated computing platform evangelist for researcher and developer communities
• Understand community requirements, analyze technical requests, and identify needle-moving projects
• Bridge NVIDIA tools with community requirements and promote NVIDIA tools, libraries, and SDKs to Chinese researchers, developers, ISVs, and service providers
• Engage with accelerated computing, AI for Science, visualization, and Agentic AI, focusing on CAE/CFD applications
• Discover new workflows, identify blockers to ISV adoption, and report findings to product teams
• Drive early adoption of new products and support launch and go-to-market activities
• Co-architect and advise on repeatable multi-cloud, hybrid, and on-premise solutions
• Jointly scope project requirements for AI4S, Generative AI, Agentic AI, and Physical AI
• Understand integrations with ecosystems and private/hybrid platforms
• Collaborate with business development managers, solution architects, developer technology engineers, developer marketing, and product teams
• Travel as required to engage customers and communities

Developer Relations Manager – CAE, CFD

Production Engineer

• Lead a global, dynamic, state-of-the-art Service Reliability Operations center
• Provide support for NVIDIA Cloud products and services
• Partner with Site Reliability Engineering, Security Operations Center, DevOps teams, and other organizations
• Support Production Kubernetes Services with a focus on automation and reducing manual tasks
• Perform large-scale Kubernetes administration, systems administration, and security monitoring to maintain service SLAs, integrity, and reliability
• Use alerts, alarms, and observability tools to monitor, detect, prevent, and respond to incidents
• Analyze logs, metrics, and system behavior to troubleshoot issues
• Lead root cause analysis and implement effective resolutions
• Initiate and lead incident management calls
• Coordinate subject matter experts and service owners for timely incident escalation and resolution
• Develop monitors, alarms, and alerts to improve service reliability and customer experience

Senior Site Reliability Engineer, Production Engineering

Machine Learning Engineer

• Write highly tuned compute kernels for core deep learning operations, including matrix multiplies, convolutions, and normalizations
• Follow software engineering best practices, including regression testing and CI/CD flows
• Collaborate with the CUDA compiler team to generate optimal assembly code
• Collaborate with deep learning training and inference performance teams to identify layers requiring optimization
• Collaborate with hardware and architecture teams on the programming model for new deep learning hardware features
• Develop optimized code to accelerate linear algebra and deep learning operations on NVIDIA GPUs
• Deliver high-performance code to NVIDIA cuDNN, cuBLAS, and TensorRT libraries

Senior Performance Software Engineer, Deep Learning Libraries

Technical Program Manager

• Collaborate with product owners and technical leads to identify and collect requirements for next-generation AI Factories
• Build, supervise, and complete long-term programs, including schedules, resourcing, and checkpoints
• Work with data center and hardware teams to develop solutions and mitigation strategies
• Lead planning with internal partners on capacity demands, engineering roadmaps, and data center expansions
• Own end-to-end delivery of 100MW+ AI factory data center deployments from construction readiness through commissioning, turn-up, and operational handoff
• Coordinate general contractors, colocation providers, utilities, and OEMs on electrical/mechanical scope, long-lead equipment, and site logistics
• Drive integrated readiness reviews and acceptance criteria across power, liquid cooling, networking, and platform/hardware teams
• Develop program plans for government grants and initiatives
• Translate program requirements into Basis Of Design documents
• Foster collaboration and hold team members accountable for action items and timelines

Technical Program Manager, AI Factory Infrastructure

• Integrate new communication library features into AI frameworks from proof of concept through performance analysis to production
• Analyze AI workloads and frameworks to identify multi-GPU communication requirements and opportunities
• Collaborate hands-on with teams working on the latest AI models
• Author custom communication or fused compute-communication kernels for maximum performance on NVIDIA platforms
• Conduct in-depth research to achieve SOL GPU performance
• Build fault-tolerant and elastic solutions for large-scale or dynamic AI workloads
• Collaborate with a dynamic team across multiple time zones

Software Engineering Intern, DLFW Comms

• Develop drivers and tests through the full software development lifecycle
• Work with software engineers, hardware engineers, and architecture teams to implement and optimize features for diagnostic solutions used in various system-on-chip use cases
• Triage, debug, and implement fixes in the software stack
• Communicate with peers throughout the company, as well as customers and partners
• Design, develop, and debug the diagnostic software stack used for CPU Tegra/Vera chips and products
• Write device drivers to produce high-quality, reliable diagnostic software for NVIDIA and customer data center and automotive products

Senior System Software Engineer, CPU

• Work with China’s industrial and research communities to integrate NVIDIA GPU-accelerated computing solutions
• Serve as a technical business development and accelerated computing platform evangelist for researcher and developer communities
• Understand community requirements and analyze technical requests
• Integrate new or expand existing solutions
• Co-architect and advise on repeatable solutions
• Jointly scope project requirements for AI for Science, Generative AI, Agentic AI, and Physical AI
• Support Enterprise AI developer communities, focusing on Agentic AI, agent skills, post-training, and platform-level solution development
• Promote NVIDIA tools, libraries, and SDKs with China researcher and developer communities, ISVs, and service providers
• Identify high-impact projects and blockers to ISV adoption, reporting findings to product teams
• Drive early adoption of new products and support launch and go-to-market activities
• Collaborate with business development managers, solution architects, developer technology engineers, developer marketing, and product teams
• Develop scalable multi-cloud, hybrid, and on-prem enterprise AI solutions
• Engage customers and communities through conferencing tools and required travel

Developer Relations Manager – Enterprise AI

• Create impactful and relevant content, including demos, blogs, presentations, and videos
• Engage with developers, researchers, and students at online and in-person events
• Collaborate with product marketing to launch emerging technology
• Write code and share it with the developer community
• Participate in public-facing NVIDIA channels, including forums, Discord, and social media
• Help developers understand NVIDIA demos and encourage them to build their own applications
• Present at trade shows and conferences as needed