NVIDIA

Software Engineer

• Research and develop cutting-edge techniques in deep learning, machine learning, HPC (High Performance Computing), graphs and data analytics
• Perform in-depth analysis and optimization to ensure the best performance on NVIDIA current- and next-generation accelerated computing platform
• Work directly with key customers to understand the current and future problems they are solving and optimize their workloads
• Collaborate closely with architecture, research, libraries, tools, and system software teams at NVIDIA

Developer Technology Engineer – AI

Solutions Engineer

• Contribute to the development of open-source inference frameworks such as SGLang and vLLM
• Develop and optimize KV cache offloading frameworks for LLM workloads
• Drive R&D on compute performance in distributed training
• Study computational challenges in machine learning systems

Senior Deep Learning Solution Architect

• Lead presales and architecture engagements with AI industry customers, focusing on GPU servers, AI clusters, and large-scale training/inference platforms built on NVIDIA HGX, GPU systems, and reference architectures
• Design and validate end-to-end AI data center solutions, including server platforms, storage connectivity, and high-performance networking based on Spectrum, Quantum, ConnectX, and BlueField
• Define system architectures for AI supercomputing, LLM training, and inference workloads, including node configuration, GPU topology, PCIe/NVLink considerations, and network design
• Support business teams in exploring, developing, and deploying NVIDIA server and GPU solution opportunities, from early technical discovery through POC and production rollout
• Own and execute POCs and hands-on labs that validate GPU server performance, scalability, reliability, and interoperability across compute, storage, and network domains
• Troubleshoot complex end-to-end issues involving GPU servers, firmware, drivers, operating systems, and networking stacks, and drive fixes with internal R&D and partners
• Provide structured feedback on platform features, system requirements, and customer needs to server OEMs, engineering, and product teams to improve NVIDIA AI platforms and ecosystems

Senior Solutions Architect, GPU System

Security Engineer

• Design and operate telemetry ingestion pipelines that collect and process data from endpoint, identity, network, cloud, and other enterprise security sources.
• Normalize and enrich telemetry into structured datasets using standardized schemas and entity models so signals from different systems can be correlated consistently.
• Build and maintain data models and graph ready structures that connect users, devices, identities, and activity across the security ecosystem.
• Provide governed access to security datasets through APIs, query interfaces, and streaming pipelines used by Detection, Automation, AI, and Analytics teams.
• Define lifecycle and retention strategies across hot, cold, and archive storage tiers to balance performance, scalability, and cost.
• Work closely with enterprise data engineering and security engineering teams to align on architecture, data fabric strategy, and shared platform capabilities.
• Maintain clear documentation of data sources, schemas, and entity definitions so teams across NVIDIA can reliably build on the platform.

Security Data Engineer

Developer Relations

• Lead and develop quantum computing developer and ISV strategy with cross functional teams: Product, Engineering, Applied Research.
• Evangelize and directly engage target collaborators.
• Discover high impact problems NVIDIA can uniquely solve that create new market paradigms.
• Drive early adoption of new products and support launch and go-to-market activities.
• Host developer and customer evangelism events: meetups, hackathons, lectures.
• Speak at relevant scientific, technical and industry conferences.

Developer Relations Manager, Quantum Computing

• Collaborate with developers and researchers to optimize performance in diverse workloads
• Profile, analyze, and optimize CPU performance
• Contribute to open-source frameworks and performance libraries
• Provide insights to shape next-generation CPU designs

CPU Performance Developer – Technology Engineer

Engineer

• Lead and drive system bringup for GPU-centric server platforms in factory and data center environments
• Design and implement end-to-end factory workflows, including firmware flashing sequences, security provisioning, and deployment of software mitigations
• Collaborate cross-functionally with data center architects, ODMs, and OEMs to define factory and data center requirements that ensure efficient and reliable production ramp
• Champion reliability, debuggability and optimization in firmware, diagnostic and deployment tool design
• Use AI tools to automate functionality and improve automation
• Troubleshoot at speed of light, working closely with system bring-up teams on next generation AI systems to debug and resolve issues during bringup and deployment

Senior System Software Bringup Engineer

• Assist and advocate for developers at a major Cloud Service Provider, encouraging the use of NVIDIA platforms
• Accelerate key workloads by demonstrating innovative solutions that integrate the NVIDIA stack into developer tools, products, and workflows
• Design and recommend technical enablement resources—such as sample code, demos, guides, and pipelines—that make NVIDIA technologies more accessible and practical for real-world use
• Support partners and startups through onboarding, integration, and co-innovation within NVIDIA programs, helping them deliver breakthrough applications
• Track and map developer ecosystems to uncover growth opportunities, influence technology strategies, and guide product adoption
• Partner with engineering, product management, marketing, and solution architects to build developer engagement programs and optimize go-to-market approaches
• Collaborate with partner technical leaders and decision-makers to align on goals, resolve challenges, and champion guidelines for reliable integrations
• Represent the voice of partners by providing practical feedback and insights to NVIDIA product and engineering teams, crafting roadmaps with real-world use cases.

Developer Relations Manager, Cloud Service Provider

• Maintain and scale fuzzing infrastructure, onboarding new fuzzers, optimizing coverage and performance, and collaborating cross-functionally with security, QA, and product teams to integrate fuzzing into development workflows.
• Design, develop, and integrate security infrastructure for GPU firmware signing, key management and derivation services, incorporating HSMs and collaborating with hardware and software engineers around the world.
• Evangelize and implement AI powered technologies and workflows to enhance developer experience, productivity, and code quality; exploring opportunities for AI assisted testing, code generation, and intelligent automation.
• Develop and automate regression testing platforms and tools to improve productivity, reliability, and coverage across GPU security components and workflows.
• Design, build, deploy, and monitor security automation frameworks and services (e.g., signing, key management, fuzzing automation), integrating with CI/CD pipelines and Kubernetes-based infrastructure.
• Build out design verification, simulation, quality, and developer workflow capabilities for the GPU Systems Software teams.

Software Engineer – Security Tools and Infrastructure

• Assist in supporting industry accounts and driving research/influencing/new business in those accounts
• Assist researchers/engineers on their GPU applications
• Deliver technical projects, demos, and client support tasks as directed by the Solution Architecture leadership team
• Provide technical support for GPU system deployments
• Be an industry thought leader on integrating NVIDIA technology into applications built on Deep Learning, High Performance Data Analytics, Robotics, Signal Processing and other key applications
• Be an internal champion for Data Analytics, Machine Learning, and Cyber among the NVIDIA technical community

Solution Architect – AI Labs

Manager

• Establish Alpasim and AlpaDreams as the open-source standard for neural simulation in AV, and scale the team and community to get there
• Take the latest research in neural rendering, simulation, and learning and work it into a modular architecture that supports fast exploration of this space
• Own product and engineering excellence — performance, scalability, reliability, developer experience, CI/CD, release management
• Partner with research teams to translate breakthroughs into production-ready platform capabilities
• Drive the research-to-production pipeline: take fragile prototypes and ship them as things developers can depend on

Senior Manager, AlpaSim – AlpaDreams Production

Sales

• Responsible for NVIDIA's software solutions for the Accelerated Datacenter for dedicated regions within EMEA
• Develop and maintain in-depth knowledge of NVIDIA Go to market strategies, competitors and market landscape
• Engage and develop deep V and C level relationship with customers
• Work with various groups such as account teams, solution architects, marketing, sales operations, and partner sales
• Contribute to and be responsible for software revenue growth in your assigned regions
• Build effective collaborations for making revenue generating opportunity management, promotions, building actions and training
• Co-selling and pro-active engagement on end user opportunities with NVIDIA account team, OEMs, Channel Partners and VARs
• Communicate NVIDIA technology impact and value to the geo

General Account Software Sales Specialist

• Validate the industry’s leading processors for deep learning, gaming, and high performance computing.
• Understand the design and implementation and bridge your knowledge to bring-up and productization
• Manage the validation of chip features and lead debug of observations on Silicon.
• Work multi-functionally with ASIC, SW, System, Characterization and ATE teams to accomplish your tasks.

Senior Silicon Validation Engineer

• Own the development of connectivity reference designs based on requirements from cluster architecture, network engineering, infrastructure software and product hardware teams
• Build and develop comprehensive documentation, including detailed rack elevations and network architecture diagrams and cabling point-to-point list
• Support projects throughout design and deployment phases
• Serve as the primary engineering support, closely collaborating with deployment and field teams to ensure successful cluster build-out and operation
• Strategically co-design the cluster with power and cooling infrastructure teams, ensuring a thorough understanding of all facility architectural requirements (Arch, power, cooling)
• Work with hardware, network and security teams to translate software stack requirements into physical requirements: hardware selection, fault domain, network architecture
• Develop new solutions and products in the connectivity space to accelerate the deployment of large scale AI Factories

Senior Data Center Connectivity Engineer

Full-stack Engineer

• Take ownership of daily cluster failures and issues, troubleshooting them promptly to maintain optimal cluster availability and performance.
• Manage updates to the site controller management nodes.
• Manage the rollout and rollback of cluster software and firmware updates, ensuring smooth transitions and minimal disruptions.