Jobs at NVIDIA

Lead cross-functional compiler software programs from concept to delivery, coordinating global teams, tracking risks and schedules, and improving development processes. Present status to executives, drive Agile and Waterfall projects, resolve technical/resource conflicts, and implement process and tool automation to ensure timely product releases.

Conduct foundational research in networking and system architecture for large-scale distributed AI and GPU systems. Design network architectures, algorithms, routing, congestion-control, scheduling, topology, and telemetry-driven control mechanisms, including AI/ML-based approaches. Build prototypes and simulations, publish research, develop patents, collaborate with academia, and define technology directions for future products. The role requires a relevant PhD, strong systems and networking research, programming and prototyping skills, and experience with AI/ML methods for systems.

Lead operations for a global events organization: manage multi-million dollar budgets, build operational processes/tools and reporting, evaluate event tech stack, coordinate cross-functional planning, remove bottlenecks, and drive high-priority initiatives to improve portfolio performance and scalability.

Lead customer solution architecture and application engineering for NVIDIA embedded and automotive systems. Collaborate with hardware, firmware, software, sensor validation, and AI teams to define system requirements, integrate SoC solutions, optimize performance, power, thermal, and mechanical characteristics, and support customers from product introduction through mass production. Lead partner enablement and multidisciplinary technical teams while developing architectures, roadmaps, documentation, and validation plans.

Conduct operational and compliance audits, including risk assessment, planning, testing, fieldwork, reporting, and remediation follow-up. Evaluate business processes, internal controls, governance, and third-party risks across global technology operations. Identify root causes, recommend improvements, influence process owners, and monitor action plans. The role requires collaboration with business leaders, strong interviewing and critical-thinking skills, and up to 10% domestic and international travel.

Develop production-grade multimodal AI systems for L3/L4 autonomous vehicles. Build sensor-fusion and spatiotemporal world models combining camera, LiDAR, radar, navigation, and vehicle-state data. Create multitask models for road understanding, occupancy, perception, prediction, and planning; develop scalable training and evaluation pipelines; investigate foundation-model approaches; optimize models for real-time NVIDIA hardware; and collaborate across AV engineering teams to deploy robust systems.

Lead the strategy definition and implementation for NVIDIA Infrastructure Specialists professional services programs. Coordinate field and headquarters teams, manage timelines, deliverables, resources, risks, objectives, and KPIs, and improve operational workflows and reporting infrastructure. Facilitate cross-functional communication and maintain accurate program records using operational systems. The role supports large-scale AI Factory deployments and requires extensive program management experience in technical operations or professional services.

Leads OEM sales growth for NVIDIA technologies through partner relationships, cross-functional team leadership, go-to-market strategy, C-suite engagement, strategic opportunity development, product roadmap coordination, partner compliance, server design qualification, marketing alignment, and forecasting. The role focuses on expanding NVIDIA’s partner portfolio and achieving revenue and business objectives across enterprise data center markets.

Own the roadmap and delivery of AI infrastructure resilience platform features, including telemetry, health checks, attribution, observability APIs, and deployment experiences. Translate developer needs into product strategy, collaborate with engineering on architecture and execution, engage open-source contributors through GitHub, and align product, marketing, field, and engineering teams. The role requires deep technical expertise in AI infrastructure, Kubernetes, developer platforms, or related systems, plus extensive product management or engineering experience.

Develop embedded networking software for NVIDIA Spectrum-X products. Responsibilities include debugging complex networking issues, building diagnostic tools and processes, collaborating with global engineering and product teams, and engaging directly with customers to address technical requirements. The role requires strong C and Python programming on Linux, embedded networking experience, analytical problem-solving, leadership in AI-native software development, and effective communication.

Design and build intelligent compiler systems, compiler-oriented agents, code transformation workflows, and numerical verification infrastructure. Develop systems for low-level IR reasoning, code generation, optimization, differential testing, regression detection, and correctness validation across GPU-centric workloads. Collaborate with compiler, CUDA, runtime, library, and hardware teams to integrate capabilities into NVIDIA products while optimizing performance, scalability, and numerical correctness.

Build and operate production agentic AI systems for executive IT insights. Develop conversational analytics agents, connect governed enterprise data through MCP, create Slack and Microsoft Teams delivery integrations, and implement validation layers that prevent hallucinated or inaccurate recommendations. Translate data into actionable portfolio and operational guidance for CIO and VP audiences while collaborating with data warehousing, AI engineering, and reporting teams.

Lead end-to-end planning and execution of CEO and senior executive events, including global keynotes, executive meetings, travel logistics, budgets, production, security, vendors, and cross-functional coordination to create high-profile, memorable experiences.

Conduct GPU performance, image quality, power, and application benchmark testing across AI, LLM, and professional visualization workloads. Bring up and debug hardware, develop Python automation tools, analyze competitive and internal performance data, validate test results, and produce reports that guide product initiatives and business decisions. Collaborate with marketing, architecture, and engineering teams while managing multiple technical projects.

Lead creative operations and account program management for NVIDIA’s internal clients. Define project scope, plans, schedules, resources, reviews, and quality assurance while coordinating creative teams, business units, cross-functional partners, and contractors. Manage multiple campaigns across email, print, social, mobile, events, video, 3D, motion graphics, banners, and websites. Resolve risks, communicate status, forecast resources, and ensure high-quality, on-time delivery.

Test optical packages for NVIDIA GPUs and SOCs using advanced optical equipment. Develop and update testing methodologies, equipment, documentation, and standardized procedures. Collect and visualize optical parameter data from test chips, define testing requirements with cross-functional teams, and solve complex manufacturing and optical systems problems.

Lead the design, automation, and operation of scalable Linux infrastructure supporting networking software development and testing. Build infrastructure-as-code, configuration management, self-service tools, monitoring, and reliability practices across physical servers, networks, virtualization, containers, and storage. Diagnose complex hardware-to-application issues, establish operational standards, collaborate across teams, and mentor engineers while driving infrastructure initiatives to completion.

Develop and optimize machine learning compilers, AI systems, and compiler abstractions for NVIDIA hardware. Build agent-driven automation for machine learning system development, co-design compiler and agent solutions, optimize AI workloads, and collaborate with software and hardware engineering teams. The role focuses on ML compiler technologies, LLM inference and training, GPU acceleration, and productizing machine learning systems.

Designs and executes manual and automated tests for NVIDIA networking switch software and firmware. Reviews requirements, maintains lab infrastructure, develops test automation, performs regression, performance, functional, and security testing, reports and reproduces defects, verifies fixes, and tracks release quality. Requires knowledge of QA methodologies, network switch configuration, Linux administration, engineering lab environments, and software release workflows. Python or other scripting experience is preferred.

Own end-to-end software integration across firmware, BSP, drivers, GPU software, services, and release systems. Lead system-level debugging of boot failures, crashes, resets, power transitions, performance regressions, and update issues. Analyze logs, traces, crash dumps, and hardware diagnostics to identify root causes, automate failure classification, integrate partner software, and coordinate cross-functional resolution across firmware, kernel, hardware, architecture, and OS teams.