NVIDIA

Mechanical Engineer

• Develop shared verification code and solutions to be widely used by the chip design team.
• Develop groundbreaking methodologies to create a flawless experience for verification engineers to keep the focus on new problems.
• Collaborate with the design automation team to provide end-to-end solutions that combine verification, simulation, and automation.
• Get in touch with EDA vendors to learn about cutting-edge tools/technology and apply them into our verification process.
• Understand the design, define the verification scope, develop the verification infrastructure and verify the correctness of the design.
• Collaborate with designers, verification specialists to accomplish your tasks.
• Develop training sessions.

Chip Design Verification Engineer

Security Engineer

• Collaborate across the company to guide the direction of platform security and develop a long-term roadmap for a flexible HW Root of Trust solution that will be integrated into our products, working with hardware, software, research and marketing teams.
• Research, design, and develop architecture solutions meeting internal and external security requirements and standards.
• Review architectural, microarchitectural and verification specifications published by internal teams to ensure all IPs align with platform security requirements.
• Work with customers, partners to identify and address security issues and threats.

Senior Security Architect – Hardware

• Build out speed and reliability features from on-chip building blocks
• Own design-to-silicon correlation
• Verify the codesign
• Use AI as a force multiplier
• Drive decisions across the silicon-to-system boundary
• Collaborate with architecture, VLSI, ASIC, firmware, and product teams

Senior Speed and Reliability Codesign Engineer

Architect

• Define and architect new GPU hardware features for future deep learning and parallel processing workloads.
• Drive microarchitectural exploration across key areas such as compute pipelines, memory hierarchy, data movement, synchronization, and performance efficiency.
• Analyze workload behavior and translate bottlenecks into clear architectural requirements and hardware feature proposals.
• Evaluate performance, power, area, complexity, and programmability tradeoffs for new architectural directions.
• Develop and use functional and performance models to study new features and refine the architecture before implementation.
• Work closely with RTL, design, verification, compiler, and software teams to ensure successful execution from architecture definition to productization.
• Create clear architecture specifications, validation plans, and success criteria for the features you define.
• Be ready to learn, dig deep, and work across the full stack when required - from workloads and models to RTL and silicon.

Senior GPU Architect, Deep Learning

• Embedded SRAM design: Transistor-level circuit design, supervising layout implementation, physical and logical verification, and debug of SRAM macros.
• SRAM compiler development: Envisioning, defining, and coding more efficient ways to automate the simultaneous assembly and validation of multiple unique SRAM macros using NVIDIA's extensive compute resources.
• Advanced development: Exploring the potential of future process nodes and developing techniques to achieve optimal power, performance, and area characteristics.
• Guiding SOC design, silicon test, and productization efforts: Collaborate with SOC design partners to help them achieve their overall performance and cost goals, guide the silicon test and characterization efforts, and working with productization teams to prepare new silicon for the demanding requirements of real-world applications.

Senior SRAM Circuit Design Engineer

Business Development Rep

• Own the end-to-end business development strategy
• Build go-to-market plans for NVIDIA Metropolis across target verticals
• Identify and develop new business opportunities within the ecosystem
• Hands-on familiarity with NVIDIA Metropolis platform components
• Direct experience driving Physical AI or IIoT adoption in industrial environments
• Established network of ISV, SI, and enterprise relationships in various sectors
• Understanding GPU infrastructure and accelerated computing economics
• Experience working within or alongside a platform company's ecosystem

Business Development Manager

Solutions Engineer

• Collaborate with NVIDIA Cloud Partners to create, implement, and deliver on NVIDIA's innovative hardware and software solutions.
• Partner with SAs, Account Managers, Engineering, Product, and business leaders to align on strategies, assess technical needs, secure business opportunities for NVIDIA.
• Become the primary technical driver for customers during the design, development, construction, integration, and production of GPU Cloud infrastructure and applications throughout the entire customer lifecycle.
• Conduct regular technical customer meetings for project/product details, feature discussions, intro to new technologies, and debugging sessions.
• Work closely with customers to build and adopt NVIDIA solutions including PoCs to address critical business needs covering infrastructure, libraries, and applications.
• Prepare and deliver technical content to customers including presentations, workshops, reference architectures, tutorials, publications.
• Up to 40% travel may be required.

Senior Solutions Architect – Telco

Program Manager

• Define and lead the long-term strategy, roadmap, and governance model for the NVIS Knowledge Management program.
• Guide the creation of the Knowledge Base platform into the definitive reference for deployment, operational, and technical documentation across NVIS.
• Establish program metrics and executive dashboards to measure adoption, content quality, knowledge coverage, operational health, and business impact.
• Lead continuous improvement initiatives that simplify knowledge creation, improve discoverability, and increase organizational adoption.
• Champion AI-enabled knowledge management, intelligent search capabilities, and automated content generation workflows.
• Partner closely with NVIDIA Training & Education to align technical documentation, learning content, and enablement programs.
• Drive organization-wide knowledge adoption through communications, organizational change, executive reporting, and engagement strategies.
• Lead a small Knowledge Management team, providing direction, prioritization, and operational leadership while encouraging continuous improvement.
• Represent NVIS within WWFO and influence enterprise-wide knowledge management practices and platform direction.

Knowledge Management Program Manager

Customer Success Manager

• Serve as the primary post-sale relationship owner for a portfolio of U.S. federal and civilian agency customers
• Develop and execute tailored Customer Success Plans that align NVIDIA AI solutions to each agency's mission priorities
• Lead regular Executive Business Reviews and agency-level health check-ins
• Drive software adoption and usage expansion across NVIDIA AI Enterprise, Run:AI, Omniverse, and hardened AI container deployments
• Identify and proactively manage customer health risks
• Partner closely with federal system integrators, OEM partners, and prime contractors
• Serve as the voice of the customer internally
• Support renewal readiness by ensuring customers are achieving their defined success metrics

Senior Customer Success Manager

Machine Learning Engineer

• Design and build PyTorch components that run efficiently on supercomputers with 1000s-100ks of GPUs
• Collaborate with NVIDIA’s hardware and software teams to improve the overall GPU performance in PyTorch
• Design, build and support production AI solutions used by enterprise customers and partners
• Work with internal applied researchers to improve their AI tools

Senior Software Engineer, PyTorch – Deep Learning

Technical Writer

• Build and refine OpenUSD -based scenes, demos, and reference workflows that combine CAD, simulation, and other technical data into clear, visually compelling experiences in NVIDIA Omniverse.
• Translate complex engineering outputs into visual narratives through scene composition, materials, lighting, rendering, camera setup, and interaction design so technical audiences can more easily understand the workflow and results.
• Work across engineering, product, and technical marketing teams to prototype reusable content that supports demos, technical storytelling, enablement, and launch moments.
• Develop workflows for bringing multiple data types into OpenUSD, including geometry, attributes, time-based data, fields, and volumetric or point-based representations, while preserving technical fidelity and usability.
• Create example scenes and narrative content that show how NVIDIA workflows connect design, simulation, analysis, and visualization, with an emphasis on clarity, reuse, and visual polish.
• Partner with domain experts to shape scenes that are not only accurate, but also engaging and easy to explore across live demos, booth experiences, and developer-facing content.

Senior Technical Marketing Engineer – Content Specialist

Analytics Engineer

• Developing novel, parallel algorithms to accelerate core problems in data processing and power the next generation of data center workflows
• Implementing solutions in C++ and CUDA
• Contributing to open source projects, such as cuDF, Velox, Presto and Spark
• Benchmarking, profiling, and optimizing code
• Working closely with the world’s top experts in GPU hardware, software and workflows

Senior Software Engineer, C++, CUDA – Analytics, Data Intelligence

• Build, lead, and continuously improve the NPN Rebate Program, including program structure, payout tiers, eligibility criteria, and performance thresholds that incentivize partner growth and drive measurable revenue outcomes.
• Build and provide assets for company-wide and outside applications to improve partner benefits programs.
• Engage with partners and internal team members to provide training and mentorship on program benefits.
• Partner with sales and business leadership to identify and develop key program initiatives to achieve business goals.
• Carry out and support regular reporting and business reviews with fellow team members within the company.
• Drive program communication strategy to increase program awareness, benefits, and participation requirements.

Rebates Program Manager

Systems Engineer

• Lead end‑to‑end performance and scalability analysis across the Kubernetes‑based accelerated runtime stack (control and data planes)
• Design and contribute upstream architectural changes to the Kubernetes control plane and related projects
• Improve container startup and cold‑start latency to enable smooth, low‑latency inference scaling on Kubernetes across thousands of GPU nodes
• Assess, improve, and contribute to open‑source projects that make Kubernetes an outstanding platform for AI workloads
• Advance scalability and performance of confidential containers on Kubernetes
• Use DSX and related large‑scale simulation infrastructure to model full AI‑factory deployments
• Collaborate with AI researchers, developers, customers, and upstream communities to design automated, at‑scale workload tests
• Document methods and results clearly and present findings internally and at industry events

Senior Systems Software Engineer – Accelerated Kubernetes Performance and Scale

Full-stack Engineer

• develop a deep, shared understanding with NVIDIA's early-adopter engineering teams
• identify the friction points where agentic workflows would have the highest impact
• iterate with teams on proof points to validate or revise plans together
• use technical judgment to distinguish durable architectural opportunities from "tech du jour" hype
• agent-ify compiler infrastructure to enable autonomous agents to make high-dimensional optimizations
• closed-loop validation on real hardware
• integrate systems into git-native workflows and CI pipelines
• contribute to cross-org collaborative group sharing reusable agentic methodology