Jobs at NVIDIA

Develop GPU-accelerated techniques for generative AI training and inference, optimize algorithms and performance across NVIDIA CPU and GPU architectures, contribute to frameworks, libraries, and open-source projects, and collaborate with developers, researchers, and hardware and software engineering teams. The role focuses on LLMs, diffusion models, multimodal systems, low-level optimization, and communicating innovations through technical publications and industry conferences.

Develop and optimize NVIDIA’s deep learning inference ecosystem, including TensorRT and related open-source frameworks. Build benchmarking workflows, analyze performance, implement graph compiler features, frontend operators, code generators, and optimized model pipelines. Improve quantization, scheduling, memory management, distributed inference, and model performance across NVIDIA GPUs and edge accelerators while collaborating on generative AI, robotics, automotive, vision, and speech applications.

Design and develop C/C++ software for NVIDIA NIC and DPU platforms. Build monitoring, debugging, performance-analysis tools, libraries, and reference applications; optimize throughput, latency, scalability, and efficiency; and contribute to networking offload and acceleration capabilities. Collaborate across architecture, firmware, hardware, validation, and software teams throughout the product lifecycle. Lead complex feature development, architecture, debugging, and technical communication.

Build and operate automation and tooling for large-scale NVIDIA GPU infrastructure. Responsibilities include bare-metal provisioning, hardware validation, firmware and software upgrades, cluster lifecycle management, BMC and Redfish integration, failure diagnosis, reliability engineering, incident response, and automated repair. The role works across hardware, networking, Linux, Kubernetes, data center operations, and partner teams to safely bring GPU capacity into production.

Design and implement high-speed mixed-signal interface circuits, including transceivers and PLLs, for next-generation NVLink products. Responsibilities include circuit design, simulation, verification, floorplanning and layout mentorship, silicon characterization, debugging, product implementation, and cross-functional collaboration. The role requires deep-submicron CMOS expertise, lab instrumentation experience, and leadership of design teams.

Develop autonomous driving systems that fuse mapping and perception data into real-time 3D world models. Build BEV models, occupancy grids, obstacle representations, and occlusion masks to support mapless navigation and scenario understanding. Collaborate with perception and planning teams, write reliable production-quality code, and apply automotive safety practices. The role also involves advanced computer vision, geometry, sensor calibration, and state estimation algorithms for autonomous vehicles.

Develop and optimize GPU-accelerated deep learning inference software for LLM, multimodal, and generative AI models. Improve performance across NVIDIA GPUs and edge SoCs, contribute to inference frameworks and libraries including vLLM, SGLang, FlashInfer, and PyTorch, and implement production-ready model-serving pipelines using CUDA and related GPU technologies. Collaborate with framework and hardware teams to deliver scalable, high-performance inference solutions.

Lead forecasting, planning, and product margin analytics for GeForce FP&A. Partner with product teams on cost and configuration analysis. Build and deploy AI/ML-enabled analytical tools, predictive models, and real-time dashboards. Provide timely financial insights and support senior leaders in a fast-paced environment.

Drive sales forecasting accuracy, pipeline health, data integrity, and operational efficiency across a global sales organization. Responsibilities include reconciling CRM, financial, and forecasting systems; maintaining Salesforce and forecasting platforms; developing performance metrics; supporting sales teams; leading cross-functional forecasting projects; and contributing to AI/ML forecasting, process automation, and analytics initiatives.

Lead technical engagements with OEM and deployment partners to design, validate, and deploy scalable NVIDIA AI infrastructure. Map customer workloads to NVIDIA hardware and software, co-design architectures, resolve complex technical issues, drive platform adoption, and influence product priorities. Lead AI Factory build-readiness execution, deployment validation, technical enablement, and issue resolution across large-scale GPU infrastructure deployments. Travel up to 50% is required.

Direct end-to-end supply planning for NVIDIA’s Boards and Systems products, translating demand and business priorities into actionable plans and customer commitments. Build integrated planning across chips, networking, memory, capacity, and manufacturing; improve accuracy using BOM, yield, cycle-time, and capacity inputs; resolve constraints; deploy advanced planning methods; and lead a global planning team through mentoring and capability development.

Develop and optimize GPU-accelerated algorithms, data structures, libraries, applications, and software environments for federal-sector applications. Collaborate with application developers and NVIDIA architecture, research, libraries, tools, and system software teams to improve performance and developer productivity across current and next-generation GPU architectures. The role includes occasional conference and developer-site travel.

Lead software safety for AI-based autonomous vehicle systems across NVIDIA’s DRIVE and Halos platforms. Define and verify safety requirements, perform system and architectural safety analyses, develop safety plans and certification evidence, improve AI safety processes, and support interactions with customers, regulators, assessors, and standards organizations. The role covers safety-critical software, embedded platforms, autonomous systems, and certification activities.

Design and build production tools, content pipelines, DCC integrations, artist-facing applications, and AI-enabled agentic workflows. Responsibilities include architecture, implementation, deployment, monitoring, testing, failure recovery, API design, production support, and technical leadership. The role integrates AI models with creative software and internal services, supports content authoring through delivery, collaborates with artists and engineers, mentors team members, and improves production workflows.

Drive adoption of NVIDIA GPU-accelerated computing solutions among China’s research and developer communities. Advise partners on cuOpt, graph optimization, databases, data processing, AI, and related ecosystems; identify technical requirements and adoption barriers; co-architect repeatable solutions; support product launches and go-to-market activities; and collaborate with business development, engineering, marketing, product, and customer teams.

Leads North American logistics execution programs, optimizing transportation, packaging, equipment utilization, capacity, and service reliability. Manages 3PL and carrier performance, cross-functional initiatives, site and lane launches, TMS and ERP implementations, business continuity planning, and continuous improvement using Lean and Six Sigma. Develops logistics strategies, dashboards, KPIs, SOPs, and AI or automation capabilities while influencing suppliers and internal teams to improve delivery speed, quality, capacity, and cost.

Lead design, automation, and operation of a scalable, secure Linux platform across physical, virtual, and cloud environments. Build IaC, provisioning, patching, security hardening, and lifecycle automation. Deploy and operate cloud infrastructure, integrate hybrid environments, and collaborate with engineering teams to improve platform reliability and maintainability.

Develop and integrate cybersecurity features into autonomous vehicle platform software, spanning sensor abstraction, data processing, middleware, embedded systems, and cloud infrastructure. Conduct threat modeling and security architecture analysis, manage product security requirements, guide security governance, and collaborate across hardware, software, safety, performance, algorithms, and cloud teams. Build scalable, performant system software using C++, C, and Python across Linux, QNX, ROS, and real-time environments.

Lead technical program management for NVIDIA’s LPU SDK software initiatives. Responsibilities include defining execution plans, managing priorities and dependencies, tracking risks, coordinating cross-functional engineering teams, reporting program status, moderating technical discussions, analyzing program metrics, and driving on-time delivery. The role also serves as a liaison between developers and customers while improving processes and supporting enterprise software programs.

Designs, develops, implements, and supports enterprise Anaplan planning solutions. Partners with business and IT teams to gather requirements, build models, manage integrations, deliver enhancements, and oversee testing, deployment, adoption, and ongoing value realization. The role also manages project work and applies Anaplan lifecycle standards across solution design and implementation.