NVIDIA

Solutions Engineer

• Own the creation of scalable datacenter solutions for enterprise AI/ML systems
• Craft detailed requirements for pioneering infrastructure patterns and datacenter wide architectures
• Create and validate cluster designs
• Collaborate closely with other experts in compute, software, and storage
• Lead multi-disciplinary projects
• Engineer on-premises cloud-native solutions
• Showcase multidisciplinary understanding of network design
• Conduct TCO analysis

Senior Solutions Architect – Enterprise AI

Systems Engineer

• Design, implement and debug changes in the NVIDIA SW stack
• Follow the devices through the development process
• Collaborate with teams from all around the globe

System Software Engineer – GPU, SOC

Mechanical Engineer

• Develop innovative HW, GPU and system designs to extend the state of the art performance and efficiency.
• Understand the design and implementation, develop methodology and infrastructure to drive Performance, Power and Area (PPA) improvements.
• Execute and deliver fully verified, high performance, area and power efficient RTL to achieve design targets.
• Collaborate with architects, designers, verification and VLSI teams to craft the industries' top performing GPUs.

Senior ASIC Design Efficiency Engineer

Blockchain Engineer

• Design, build, deploy, and run infrastructure services & manage the software life cycle in scope to meet our business goals.
• Participate in the definition of our internal facing service level objectives and error budgets as part of our overall observability strategy.
• Eliminate toil or automate it where the ROI of building and maintaining automation is worth it.
• Practice sustainable blameless incident prevention and incident response while being a member of an oncall rotation.
• Consult with and provide consultation for peer teams on systems design best practices.

Senior Software Engineer, Infrastructure Automation, Distributed Systems

Performance Marketing

• Benchmarking: Maintain a suite of CAE solver benchmarking solvers and results across NVIDIA platforms.
• Building: Collaborate with internal engineering and marketing teams as well as external partners to build product-based how-to technical content — including benchmark methodology guides, performance reference architectures, and solution briefs.
• Communicating: Deliver high-quality technical material to engineers, developers, and scientists through blogs, whitepapers, training materials, and conference presentations that highlight benchmark findings and platform capabilities.
• Enabling: Build high-quality training materials and documentation to help researchers and developers get the most out of NVIDIA-accelerated CAE workflows.

Senior Technical Marketing Engineer – CAE Performance

Product Specialist

• Drive revenue growth and achieve 100% quota attainment for NVIDIA's networking portfolio.
• Identify, qualify, develop, and close new networking opportunities across Enterprise accounts.
• Lead customer-facing discussions to articulate the value of NVIDIA networking solutions and position them within broader AI and data center initiatives.
• Collaborate with Solution Architects and technical teams to address customer requirements and support solution development.
• Maintain accurate opportunity tracking, pipeline management, and forecasting within Salesforce.
• Partner with OEMs, CSPs, channel partners, and ecosystem stakeholders to execute go-to-market initiatives and expand market reach.
• Coordinate complex sales motions across internal and external teams, ensuring responsiveness and alignment throughout the sales cycle.
• Develop strategic relationships with customers to understand their AI initiatives, infrastructure requirements, and business priorities across Physical AI and Financial Services industries, identifying opportunities to expand NVIDIA AI Infrastructure adoption.

Networking Product Sales Specialist

Account Manager

• Accountable for every facet of strategy development and application
• Be the key point of contact and relationship owner for a defined set of customers
• Working closely with partners, OEMs, and ecosystem partners to build and complete go-to-market plans
• Evangelizing the use of NVIDIA's platform, products and technologies to customers and partners

Senior Account Manager – Telecom, MSO, Satellite, Cloud Providers

• Work with partners to create and implement business plans driving enablement, engagement, and acceleration strategies
• Create, develop, and maintain relationships with key Energy companies and the ecosystem that supports them; think EOM, ISVs, etc
• Lead Ecosystem enablement and engagement across NVIDIA Sales, Marketing, Technical, Program, and Business Segment teams to help partners build a successful AI practice
• Present results in regular internal QBRs

Industry Partner Business Manager

Machine Learning Engineer

• Train, develop, and deploy state-of-the generative AI models like LLMs and diffusion models using NVIDIA's AI software stack
• Leverage and build upon the torch 2.0 ecosystem to analyze and extract standardized model graph representation
• Develop high-performance optimization techniques for inference
• Collaborate with teams across NVIDIA to use performant kernel implementations within our automated deployment solution
• Analyze and profile GPU kernel-level performance to identify hardware and software optimization opportunities
• Continuously innovate on the inference performance

Senior Deep Learning Software Engineer, Inference and Model Optimization

Product Manager

• Collaborating with community model builders to ensure seamless model support, early access collaboration, and go-to-market alignment.
• Tracking emerging trends in the open model space and assess technical differentiators and ecosystem impact of new releases.
• Supporting product marketing in crafting model-specific messaging and documentation - including blogs, whitepapers, case studies, and presentations, highlighting NVIDIA’s optimizations and software tools.
• Collaborating closely with internal engineering, infrastructure, and developer experience teams to enable best-in-class support for open models across inference, fine-tuning, and evaluation.
• Working onsite at least 3 days per week.
• Facilitating feedback loops between our platform and model builders to continuously improve performance, usability, and compatibility.
• Work with executives to launch new products and support keynotes.

Product Manager – Open Models

AI Engineer

• Track and understand evolving agent development patterns across NVIDIA and the broader ecosystem, maintaining current knowledge of both research and commercial products.
• Develop open-source libraries and tools which accelerate and optimize agent harnesses and frameworks ensuring top-tier performance, accuracy, quality, and stability.
• Benchmark the latest agents to identify bottlenecks and build creative solutions to increase performance, reduce cost, and improve latency.
• Work closely with teams building high-performance data pipelines, RAG systems, vector databases, and GPU-optimized training and inference workflows to deliver best-in-class agentic applications.
• Identify gaps and friction in current agent architectures, and translate insights into agentic tools that boosts developer velocity and agent quality—backed by evaluations, benchmarking, and feedback loops.

Senior Software Engineer, Agentic AI

Security Engineer

• Design and build identity, authorization, and service-trust capabilities for a collaborative cloud application.
• Translate security and access requirements into controls that are practical for users and product teams.
• Strengthen credential handling, auditing, isolation, and protection of sensitive performance data.
• Build secure, reproducible infrastructure and delivery practices for supported environments.
• Improve release safety, recovery, and operational resilience for services and persistent data.
• Establish useful security and reliability signals for incident response, resource management, and ongoing improvement.
• Partner with engineering and security teams to identify risks, validate controls, and address failures before release.

Senior Software Engineer – Identity and Security, Profiling Services

Frontend Engineer

• Build intuitive browser experiences that help engineers explore and understand complex performance data.
• Create reusable visualization and interaction patterns that remain consistent across product workflows.
• Integrate high-performance visualization technologies into a maintainable frontend application.
• Improve responsiveness and memory efficiency for large and complex datasets.
• Deliver accessible, resilient experiences across supported browsers, devices, and application states.
• Partner with backend, product, design, and quality teams to ship and validate complete user workflows.

Senior Frontend Engineer, Visualization - Profiling Services

• Design, improve, and operate scalable vulnerability management workflows across ingestion, triage, prioritization, remediation, and reporting.
• Engineer integrations across vulnerability scanners, endpoint tools, cloud platforms, asset inventory, ticketing systems, and remediation workflows.
• Build automation to reduce manual effort, improve consistency, and accelerate vulnerability response across engineering teams.
• Partner with application, infrastructure, cloud, and platform teams to clarify remediation requirements and drive issues to closure.
• Support risk-based vulnerability prioritization using asset context, exploitability, threat intelligence, and business impact.
• Embed vulnerability management practices into engineering and CI/CD workflows where appropriate.
• Track remediation progress, identify blockers, and communicate outstanding risk to technical and leadership audiences.
• Contribute to process improvements, standards, and operational playbooks for enterprise vulnerability operations.

Senior Cyber Security Engineer – Vulnerability Operation

Backend Engineer

• Design and build production backend services for interactive performance analysis and collaborative workflows.
• Improve the responsiveness, scalability, and efficiency of data-intensive product experiences.
• Develop reliable capabilities for onboarding, validating, organizing, and serving large performance datasets.
• Create durable service interfaces and data models that can evolve as product needs grow.
• Engineer resilient behavior for concurrency, partial failures, retries, and recovery.
• Establish effective testing, observability, and operational practices for the capabilities you own.
• Partner with frontend, security, product, and source-system teams to deliver complete customer workflows.