NVIDIA

• Play meaningful role in NVIDIA's effort in contributing to JAX. • Design and implement JAX core components and drive peak performance on NVIDIA products. • Work with AI applied researchers and leaders to build future-proof models • Build tools that will increase the efficiency of teams developing AI-based systems. • Work to bridge the gap between the latest in numerical computing, simulation and deep learning research and their applications in real world products.

Role Description NVIDIA is currently hiring a Senior Structural Test Engineer to join our Test Team. In this role, you will build next-generation boards and systems while collaborating with cross-functional teams and suppliers to deliver functional test hardware solutions. - Define ICT capability, hardware design requirements, and board debug capabilities, enabling structural testing at Texas CM sites. - Optimize structural test plans to identify SMT, PCB, and component issues early. - Collaborate with board designers, layout engineers, tester vendors, and fixture providers, offering DFM guidance to meet ICT requirements. - Support production bring-up and debugging, including offshore tester platform bring-up involving ICT, BSI, FCT universal testers, and more. - Coordinate test fixtures and platform automation with suppliers, contract manufacturers, and global teams. - Develop procedures, documentation, and provide technical support as needed. Qualifications - Master’s degree (or equivalent experience) in Electrical, Mechanical, Materials, or related fields. - At least 5 years of experience in ICT programming, fixture design/manufacturing, and factory testing. - Strong understanding of ICT development, hardware design, board debugging, and structural testing. - Solid knowledge of board manufacturing processes, PCB/fixture design, and proven program management capability. - Excellent communication, analytical, problem-solving, and decision-making skills. - Strong team collaboration and analytical abilities with effective work habits. - Self-starter able to complete tasks with minimal supervision. Benefits - Competitive salaries. - Comprehensive benefits package. - Equity eligibility. Company Description NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. We highly value diversity in our current and future employees and do not discriminate on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.

• Build and deploy scalable ML/AI and optimization models to enhance demand forecasting, optimize capacity allocation, and develop user-specific feature engineering for real-time cloud gaming services. • Develop reusable framework deployments for data ingestion, processing, and analysis to support dynamic user interventions for targeted business outcomes. • Acquire and apply domain knowledge of the product and software stack to identify and drive the resolution of data inconsistencies and improve model performance, especially in the context of optimization outcomes. • Identify, analyze, and interpret trends or patterns in complex data sets using supervised and unsupervised learning techniques, informing prescriptive solutions. • Design and implement improvements to real-time prescriptive scheduling pipelines, using techniques like linear programming and constraint optimization, to enhance capacity utilization and user retention. • Improve productivity of the organization by mining petabytes of data for actionable insights for business and engineering, often through prescriptive recommendations. • Collaborate with a variety of partners to understand requirements, design robust solutions, and guide the team to deliver impactful results. • Leverage agentic AI to deliver best-in-class automation and programming solutions for complex analytical problems.

• Be a technical specialist on GPU and networking products, partnering with account, program, architecture, and engineering teams to support design-in, integration readiness, issue resolution, and successful ramp execution. • Actively establish and nurture technical relationships with partner engineering teams, technical leaders, internal stakeholders, and cross-functional launch teams. • Identify customer architectures and key product requirements in the CSP/ODM AI market to successfully implement NVIDIA's solutions. • Provide primarily onsite technical support, with remote and travel-based support as business needs require, to debug hardware, firmware, software, networking, and system integration issues. • Lead the product across design-in, NPI, rack integration, validation, production ramp, sustaining support, and lifecycle transitions. • Develop technical solutions including hardware & software demos and example system builds. • Offer technical enablement to internal technical teams, account teams, program teams, and partner-facing stakeholders. • Establish strong communication channels and collaborative relationships with internal teams to ensure a positive customer experience.

• Be a technical specialist on GPU and networking products, partnering with account, program, architecture, and engineering teams to support design-in, integration readiness, issue resolution, and successful ramp execution • Actively establish and nurture technical relationships with partner engineering teams, technical leaders, internal stakeholders, and cross-functional launch teams • Identify customer architectures and key product requirements in the CSP/ODM AI market to successfully implement NVIDIA's solutions • Provide primarily onsite technical support, with remote and travel-based support as business needs require, to debug hardware, firmware, software, networking, and system integration issues • Lead the product across design-in, NPI, rack integration, validation, production ramp, sustaining support, and lifecycle transitions • Develop technical solutions including hardware & software demos and example system builds • Offer technical enablement to internal technical teams, account teams, program teams, and partner-facing stakeholders • Establish strong communication channels and collaborative relationships with internal teams to ensure a positive customer experience.

• Provide onsite support for large datacenter deployments of NVIDIA AI solutions. • 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 positive relationships and communication channels with internal teams. • Up to 30% travel may be required.

• Analyze and demonstrate HW fault metric compliance • Propose new methods and refine existing practices • Carry out analysis using classical approaches such as fault trees alongside model-based techniques • Develop automation to support the analysis of complex multi-layered systems • Analyze and interpret internal and external safety documentation for improvements • Ensure integration of the System, Software and Hardware safety analysis methodologies

• Refine developer, user, and agent journeys: Understand how developers, enterprise platform teams, partners, and customers, and their respective agents, consume NVIDIA AI software, then craft clear technical journeys supported by documentation, code examples, demos, and deployment guidance. • Showcase enterprise AI software workflows: Build demos, reference examples, notebooks, and sample applications that show how NVIDIA AI software components work together across model development, inference, RAG, agentic AI, evaluation, deployment, and operations. • Build compelling technical assets: Accelerate adoption by creating public-facing content such as product documentation, deployment guides, reference architectures, tutorials, blog posts, whitepapers, technical presentations, webinars, demo videos, and code examples. • Develop automation and docs-as-code workflows: Create repeatable examples and publishing workflows using Git-based documentation, CI/CD, scripts, templates, and AI-assisted docs or skills where appropriate. • Enable the field and partner ecosystem: Support solution architects, sales teams, cloud partners, ISVs, and ecosystem teams with technical assets that help them explain, deploy, and integrate NVIDIA enterprise AI software. • Collaborate across the stack: Work closely with Technical Marketing Engineering, Product Management, Engineering, Developer Relations, Field, and Marketing teams to turn product capabilities into practical adoption paths. • Capture feedback and improve the product experience: Use customer, partner, developer, and field feedback to identify gaps in usability, examples, documentation, deployment patterns, and product workflows. • Engage the developer and open source community: Advocate for NVIDIA AI software in developer, cloud-native, and open source ecosystems, encouraging adoption through clear examples and practical technical storytelling.

• Contribute to a platform that automates GPU asset provisioning, configuration, and lifecycle management across cloud providers • Build end-to-end automation of datacenter operations, break/fix, and lifecycle management for large-scale Machine Learning systems • Implement monitoring and health management capabilities that enable reliability, availability, and scalability of GPU assets • Manage NVLINK topography across GPU clusters • Build automated test infrastructure to qualify distributed systems for operation • Collaborate with engineering teams to ensure software integration from hardware to AI training applications

• Build and maintain infrastructure across bare-metal, virtualized, and containerized environments using advanced technologies and high-end hardware. • Drive continuous improvements across CI/CD pipelines and automation workflows. • Provide infrastructure and automation support for development and verification teams, enabling efficient development and testing processes. • Support development and integration activities for next-generation infrastructure and software platforms. • Improve reliability, scalability, and operational efficiency across Linux- and Windows-based environments.