Design, train, and optimize machine learning models for LiDAR and camera perception within the NVIDIA DRIVE AV platform. Develop end-to-end ML workflows and transition experimental algorithms into efficient production-level C++ code.
NVIDIA
126 Remote Job Openings at NVIDIA
Manage strategic relationships with Ford and Rivian to drive design wins and revenue growth in automated driving and cockpit applications. Collaborate with internal stakeholders and external R&D teams to position NVIDIA's AI and deep learning solutions within the automotive ecosystem.
Lead a team of software and production engineers to build and operate scalable GPU infrastructure for DGX Cloud. Drive execution across Kubernetes operations, automation, and incident response while partnering with cross-functional teams to improve production readiness.
Drive the deployment and integration of next-generation AI networking platforms and fabrics at strategic customer data centers. Partner with customers to guide architecture decisions and translate technical requirements into product feedback for engineering teams.
Maintain the reliability, availability, and performance of the GeForce NOW cloud gaming platform across cloud and datacenter environments. Drive observability initiatives and build automation tools to eliminate operational toil and improve service SLOs.
The manager will lead a team to operationalize NVIDIA technologies, bridging the gap between prototypes and production-ready deployments. Responsibilities include managing deployments, resolving obstacles, and collaborating with engineering teams.
The Sales Development Specialist will build a pipeline of new opportunities for the sales group by identifying and qualifying leads. They will also implement demand generation programs and maintain high-volume daily activities with prospects.
Design and optimize GPU-accelerated software for deep learning inference, focusing on LLM and Generative AI models. Contribute to open-source frameworks and libraries like vLLM and SGLang to improve model serving pipelines across NVIDIA accelerators.
Drive the deployment of end-to-end AI hardware and software solutions in customer data centers. Act as a technical advisor to strategic customers, guiding network design and providing feedback for the product roadmap.
Manage the operating rhythm and day-to-day engagement with OEM/ODM partners to ensure hardware deployment and operational execution. Drive cross-functional alignment and standardize reporting mechanisms to provide leadership visibility into program health and risks.
Design, implement, and maintain large-scale HPC/AI clusters using Infrastructure as Code and automated CI/CD pipelines. Perform complex troubleshooting from bare metal to application levels and lead technical best practices for system reliability.
Translate AI research into secure, production-grade runtime infrastructure for AI agents. This involves tracking cutting-edge research, building rapid prototypes, and designing secure-by-default workflows for enterprise builders.
Lead technical engagements to accelerate customer AI workloads and reduce infrastructure costs. Develop proof-of-concepts and debug software for NVIDIA and open-source AI frameworks.
Design and evaluate routing policies for LLM traffic and build agentic benchmarks to measure algorithm quality. Collaborate with engineering teams to integrate software across the NVIDIA accelerated serving stack and contribute to open-source repositories.
Lead the design and implementation of large-scale Kubernetes clusters with a focus on reliability, performance, and real-time monitoring. Manage the full service lifecycle from inception through deployment and maintain system health through automation and sustainable incident response.
Lead the definition, positioning, and go-to-market strategy for AI physics products, models, and frameworks. Collaborate with engineering and marketing teams to translate technical capabilities into customer value and partner enablement assets.
Support SLT NPI manufacturing activities from product bring-up through mass production. Develop automated test systems, thermal solutions, and leverage AI technologies to improve testing efficiency and yield.
The engineer will perform technical analysis and debugging of returned networking products at contract manufacturer locations. They are responsible for identifying failure trends and escalating complex systemic issues to global engineering and design teams.
Define and drive structural test plans for baseboards and systems to detect SMT, PCB, and component issues early. Collaborate with cross-functional teams and suppliers to develop automated test infrastructure and hardware solutions.
Provide onsite technical engagement and support for large-scale NVIDIA AI datacenter deployments. Act as a technical specialist for GPU and networking products to support sales account managers and establish relationships with customer architects.
Senior Platform Safety Analysis Engineer, HALOs Platforms - Autonomous Vehicles
NVIDIA
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Full Time
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8 days ago
NVIDIA
Lead the development of safety architecture and requirements for AI-powered autonomous driving platforms. Perform complex safety analyses using qualitative and quantitative methods to ensure hardware and software fault metric compliance.
Lead the design and development of end-to-end reference system stacks for 5G/6G baseband systems. Optimize CPU, GPU, and NIC sub-systems to ensure low-latency and maximum throughput while collaborating with partners and customers.
Responsible for production systems enabling large scalable GPU clusters for AI workloads, including asset provisioning and lifecycle management. Focuses on implementing monitoring, health management, and incident response to ensure maximum performance and reliability.
Manager, Solutions Architecture - Financial Services Capital Markets
NVIDIA
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Full Time
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10 days ago
NVIDIA
Lead a team of architects to drive NVIDIA's full-stack technology strategy within the Capital Markets sector of the financial services industry. Recruit and mentor technical talent while supporting business development and sales to achieve design wins.
Build and maintain automated infrastructure across bare-metal, virtualized, and containerized environments. Drive continuous improvements in CI/CD pipelines and provide automation support for development and verification teams.
Architect and scale high-performance distributed AI infrastructure using NVIDIA GPU supercomputers for diverse customers. Provide technical leadership and on-site support throughout the product lifecycle to ensure successful deployment and customer satisfaction.
Provide onsite technical engagement and support for large-scale NVIDIA AI datacenter deployments. Act as a technical specialist for GPU and networking products to support sales and establish relationships with customer architects.
Architect and build scalable RL post-training infrastructure that spans from single GPU experimentation to production across thousands of nodes. Collaborate with researchers to optimize deep learning frameworks and improve distributed runtimes like Ray and Monarch.
Serve as the primary post-sale relationship owner for U.S. federal agencies to drive the adoption and value realization of NVIDIA's AI portfolio. Develop tailored success plans and lead executive business reviews to align technology deployments with mission-critical outcomes.
Build and maintain a Kubernetes-native control plane to gather, aggregate, and normalize topology data for GPU-accelerated infrastructure. Interface with NVIDIA hardware to optimize GPU-to-GPU communication for large-scale workloads across multiple cloud providers.
Lead the infrastructure planning, physical deployment, and hardware remediation for AI factories and supercomputers. Ensure data center physical infrastructure meets NVIDIA reference architectures and industry standards through meticulous validation and vendor management.
Lead the planning, deployment, and validation of AI data center infrastructure, focusing on power, cooling, and networking systems. Ensure all physical infrastructure meets NVIDIA reference architectures and industry standards through rigorous auditing and quality assurance.
Define and drive NVIDIA's JAX strategy to ensure peak performance across heterogeneous supercomputing platforms. Lead and mentor a high-performing engineering organization while coordinating contributions across the JAX ecosystem and partnering with external open-source projects.
Senior Systems Software Engineer, Accelerated Kubernetes Performance and Scale - DGX Cloud
NVIDIA
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Full Time
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17 days ago
NVIDIA
Lead performance and scalability analysis for the Kubernetes-based accelerated runtime stack to optimize AI infrastructure. Design architectural changes for the Kubernetes control plane and contribute to open-source projects to enable hyperscale AI workloads.
Lead the regional co-sell strategy and execution across major cloud service providers including AWS, Google Cloud, Microsoft Azure, and Oracle Cloud. Drive the adoption of NVIDIA technologies by building enablement programs and managing multi-functional teams to optimize partner engagement.
Define high-level SoC subsystem architecture for LPU products and convert requirements into detailed architectural specifications for uncore and I/O. Collaborate with IP and software teams to build functional models and drive tradeoffs in bandwidth, power, and latency.
Drive the deployment of end-to-end AI hardware and software technology solutions at strategic customer data centers. Act as a technical advisor to guide network design, debug performance issues, and provide feedback for the product roadmap.
Senior Developer Relations Manager – Cloud Provider AI Factory
NVIDIA
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Full Time
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20 days ago
NVIDIA
Drive the adoption of NVIDIA's AI and computing platforms by serving as a technical advisor to cloud provider and hosting ecosystems. You will integrate the NVIDIA software stack into partner products and collaborate with internal engineering teams to inform product roadmaps.
Drive end-to-end performance and scale characterization for the NVIDIA DGX Cloud software stack, focusing on Kubernetes and GPU components. Design monitoring tools and collaborate with the open-source community to optimize AI infrastructure and reduce cost per token.
Provide comprehensive technical support and debugging for AI hardware and software products on the DGX Platform. Collaborate with Engineering and Marketing teams to improve product requirements and support methodologies.
Senior Systems Software Engineer, Kubernetes Scale - DGX Cloud
NVIDIA
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Full Time
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21 days ago
NVIDIA
Drive end-to-end performance and scale characterization for the NVIDIA DGX Cloud software stack, focusing on Kubernetes and GPU components. Design monitoring tools and collaborate with the open-source community to optimize AI infrastructure and reduce cost per token.
Partner with university researchers to advance foundation models, multimodal AI, and agentic systems using NVIDIA's accelerated computing platforms. Provide technical guidance on GPU-accelerated training, inference studies, and the development of research prototypes.
Senior Solutions Architect, AI Factory Observability and Visualization - NVIS
NVIDIA
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Full Time
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22 days ago
NVIDIA
Develop full-spectrum visibility and observability for HPC systems and AI factories to ensure optimal performance. This includes running validation tools, building telemetry surfaces, and collaborating across teams to transform complex data into actionable insights.
Partner with research universities to co-create innovative HPC and AI solutions using NVIDIA's accelerated computing platform. Architect ground-breaking workflows in computational physics and optimize AI training and inference workloads for scientific applications.
Deploy, manage, and maintain large-scale AI infrastructure for customers as a domain expert. Collaborate with internal teams to provide feedback, document workarounds, and implement AI Factory projects.
Research and implement model architecture improvements to enhance video generation fidelity and human-centric quality for world foundation models. Translate research results into production-grade checkpoints and benchmarks to improve physical AI and simulation.
The role focuses on owning the mechanical aspects of production test fixtures, jigs, and enclosures across global contract manufacturing sites. It involves managing maintenance, calibration, and NPI mechanical readiness to ensure high-volume manufacturing excellence.
Lead the GeForce business by managing AIC/OEM partners and distributors to drive sales growth and market dominance. Develop end-user demand generation programs and collaborate with gaming ecosystem partners to increase brand preference.
Lead the growth of the Federal Physical AI ecosystem by driving the adoption of NVIDIA's AI and computing platforms through strategic partnerships. Collaborate cross-functionally to develop go-to-market resources and provide actionable field insights to influence internal product roadmaps.
Senior Software Engineer – Accelerated Quantum Chemistry and cuEST
NVIDIA
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Full Time
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a month ago
NVIDIA
Architect, implement, and optimize production-grade GPU solutions for the cuEST quantum chemistry library. Collaborate with the broader community and internal teams to drive the adoption and development of GPU-accelerated electronic structure computations.
Partner with engineering and sales teams to secure design wins and optimize ML/DL models for financial services clients. Develop technical collateral and proof-of-concepts to accelerate high-performance computing workloads in capital markets.
The role focuses on enabling AI startups and enterprise customers to accelerate their applications using NVIDIA SDKs and technologies. This includes creating high-quality technical content, tutorials, and training materials to drive adoption across the developer ecosystem.
Act as a technical advisor to the Automotive and Mobility developer ecosystem to drive the adoption of NVIDIA's AI and computing platforms. Collaborate cross-functionally to integrate NVIDIA stacks into partner products and influence internal product roadmaps based on field feedback.
The role focuses on building a pipeline of new opportunities for NVIDIA's Nordic sales teams through lead management and demand generation. This includes identifying prospects via phone, email, and LinkedIn, and collaborating with marketing and sales teams to convert leads.
Develop energy-specific applications and platforms using NVIDIA technology to serve the Oil and Gas, Renewables, and Power Utilities sectors. Act as a technical advisor to partners and customers, bridging the gap between industry teams and technical implementation.
Design, deploy, and operate large-scale storage and data platforms on Kubernetes using automation and infrastructure-as-code. Develop telemetry and observability tools to ensure system health and participate in sustainable incident response and on-call rotations.
Profile and optimize end-to-end neural reconstruction and Gaussian Splatting workflows to improve speed, scalability, and reliability. Translate Python and PyTorch bottlenecks into efficient CUDA/C++ implementations while ensuring reconstruction quality is preserved.
Collaborate with internal and external teams to define system requirements for fault-tolerant quantum computing. Develop novel approaches for real-time quantum error correction and calibration across various qubit modalities.
The role involves acting as a technical consultant for ISV developers to foster the adoption of NVIDIA's AI and computing platforms. You will collaborate cross-functionally to identify growth opportunities, guide partner onboarding, and influence product roadmaps based on field feedback.
Principal Simulation Engineer, Industrial Physics and Robotics
NVIDIA
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Full Time
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a month ago
NVIDIA
Design and develop high-fidelity physically based simulation systems for robotics and industrial digital twins. Collaborate across teams to integrate advanced simulation methods into scalable GPU-accelerated computing environments.
Senior Solutions Architect, Cloud Infrastructure and DevOps - NVIS
NVIDIA
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Full Time
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2 months ago
NVIDIA
Maintain large-scale HPC/AI clusters and develop automation tooling for deployment, monitoring, and resource consumption. Collaborate with customers and internal teams to analyze and implement large-scale networking projects.
Senior Solutions Architect, Generative AI - AI Models and Systems at NVAITC
NVIDIA
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Full Time
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2 months ago
NVIDIA
Collaborate with university research labs to identify and execute high-impact Generative AI projects. Act as a strategic bridge between academic partners and NVIDIA's engineering teams to drive the adoption of NVIDIA software platforms.
Senior Solutions Architect, Physical AI and Robotics at NVAITC
NVIDIA
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Full Time
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2 months ago
NVIDIA
Collaborate with university PIs on high-impact Physical AI and Robotics research projects while championing the adoption of NVIDIA software platforms. Act as a strategic bridge between academic partners and NVIDIA's internal engineering teams to drive world-class research and institutional agreements.
Design and deploy Agentic AI applications to automate telecommunications network operations using generative models and RAG pipelines. Provide technical guidance to strategic partners and translate integration challenges into reference architectures for the NVIDIA accelerated computing stack.
Profile and optimize end-to-end neural reconstruction and Gaussian Splatting workflows to improve speed, scalability, and reliability. Translate Python and PyTorch bottlenecks into efficient CUDA/C++ implementations while ensuring reconstruction quality is preserved.
Senior Solutions Architect, Infiniband and Networking Ethernet - NVIS
NVIDIA
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Full Time
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2 months ago
NVIDIA
Build and support large-scale AI/HPC infrastructure for customers, focusing on performance, reliability, and real-time monitoring. Collaborate with internal teams to refine services and implement large-scale networking projects.
Lead research in AI for quantum algorithm discovery and drive technical collaborations with supercomputing centers and QPU builders. Develop innovative quantum-classical applications and publish impactful research to drive NVIDIA's quantum product adoption.
Manage NVIDIA Interconnect products by ensuring flawless engineering implementation, maintenance, and yield management. Coordinate with manufacturing partners and cross-functional teams to resolve product failures and scale capabilities.
Architect and optimize AI/ML pipelines for large biological foundation models using NVIDIA's accelerated computing platform. Act as a technical advisor to biopharma customers to integrate GPU-accelerated software and improve scientific discovery workflows.
Senior Solutions Architect, Simulations - Clinical Sciences and Autonomous Lab
NVIDIA
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Full Time
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2 months ago
NVIDIA
Drive innovation in healthcare and life sciences by designing and optimizing GPU-accelerated AI software for clinical sciences and autonomous labs. Partner with pharmaceutical companies to implement patient modeling, robotic systems, and biomedical agentic AI.
Lead the research, design, and implementation of security architectures for next-generation NVIDIA Networking products. Collaborate with cross-functional teams and external partners to develop hardware security primitives and trusted platforms.
Senior Technical Program Manager, Pre-Silicon Software Enablement and Workload Studies
NVIDIA
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Full Time
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2 months ago
NVIDIA
Drive NVIDIA's software left-shift program to ensure software teams have necessary infrastructure to begin development early in the silicon lifecycle. Lead cross-functional alignment between architecture, modeling, and software teams to resolve dependencies and improve pre-silicon results.
Conduct in-depth performance characterization and analysis on large multi-GPU and multi-node clusters. Triage and root-cause performance issues while building tools to visualize and analyze performance data.
Drive the adoption of NVIDIA Metropolis and Vision AI technologies by building strategic relationships with ISVs and enterprise leaders. Provide technical leadership to integrate Vision-Language Models and AI agents into real-world operational intelligence applications.
Lead contract manufacturers in the Mexico region to ensure the highest quality of complex AI hardware systems. Drive continuous improvement through supplier assessments, audits, and the implementation of quality metrics and corrective actions.
Senior Developer Relations Manager - Digital Biology Partnerships
NVIDIA
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Full Time
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2 months ago
NVIDIA
Serve as a technical advisor to the developer ecosystem in computer-aided drug discovery to drive the adoption of NVIDIA's AI and computing platforms. Collaborate with software partners to optimize applications, co-develop roadmaps, and integrate the NVIDIA stack into developer pipelines.
Manage end-to-end production infrastructure supply chain from NPI to mass production delivery. Coordinate production capacity, risk assessments, and infrastructure maintenance across multiple production sites.
The Senior Product Engineer will manage board product lifecycles, including yield management, manufacturing process optimization, and failure resolution. They will collaborate with cross-functional teams to ensure high-quality product execution across global contract manufacturing sites.
The Senior Supplier Quality Engineer will lead factory quality onsite activities, including NPI and mass production, while ensuring compliance with NVIDIA quality standards. They will also facilitate root cause analysis, manage supplier performance metrics, and drive continuous improvement initiatives across the supply chain.
You will develop, deploy, and validate AI factory environments by running and debugging complex AI/LLM workloads on GPU clusters. Additionally, you will build automation and observability tools to optimize performance, latency, and scalability for distributed training.
You will lead technical engagement efforts with defense partners to integrate NVIDIA's accelerated computing stack into autonomous aerial platforms and uncrewed systems. This involves architecting perception and planning pipelines, providing reference designs, and guiding product roadmaps for edge AI technologies.
Lead and mentor technical teams while driving AI research and strategic collaborations with academia and industry. Develop and implement NVIDIA technology-related tutorials, workshops, and demos to foster accelerated AI adoption.
The Solutions Architect will serve as a subject matter expert in AI research and engineering, driving collaborations with academia and industry. They will also lead technical projects, mentor team members, and develop educational materials to foster AI ecosystem growth.
The Solutions Architect will serve as a technical advisor to drive the design, integration, and deployment of large-scale AI and GPU infrastructure for strategic partners. They will collaborate with cross-functional teams to deliver technical content, conduct workshops, and ensure successful implementation of NVIDIA hardware and software solutions.
You will act as the technical authority and advocate for the capital markets developer ecosystem, driving engagement and adoption of NVIDIA AI solutions. This involves collaborating with cross-functional teams to deliver technical enablement resources and influencing product roadmaps based on developer feedback.
Manage end-to-end production infrastructure supply chain from NPI to mass production delivery. Coordinate capacity management, risk assessment, and maintenance activities across multiple production sites.
You will design and deploy sophisticated Agentic AI systems for top-tier retail and enterprise clients using NVIDIA's core technology stack. This role involves building reference architectures, optimizing inference performance, and enabling partner engineering teams through technical workshops and documentation.
The Solutions Architect will engage with customers and partners to deliver high-value technical solutions leveraging NVIDIA's AI, HPC, and networking platforms. They will act as a trusted technical advisor, creating documentation and educational content while collaborating with internal teams to drive customer success.
Analyze High Performance Computing (HPC) applications to identify performance characteristics and optimization opportunities. Provide technical guidance to compiler and application engineering teams to improve GPU acceleration and system performance.
You will design and implement core JAX components to drive peak performance on NVIDIA products while collaborating with AI researchers. Additionally, you will build tools to improve the efficiency of teams developing AI-based systems and bridge the gap between research and real-world applications.
You will plan and establish processes, define test requirements, and optimize production lines to successfully launch new GPU boards for datacenter architectures. Additionally, you will collaborate with cross-functional teams and contract manufacturers to ensure cost and quality metrics are met while resolving yield and test problems.
The role involves guiding partners in adopting end-to-end Agentic AI solutions and collaborating with customers and partners to deploy AI solutions at scale. Solution Architects will also assist with demos, proof-of-concepts, and knowledge sharing.
The Project Technical Delivery Manager will oversee the complete project lifecycle from initiation to close, ensuring technical requirements are met within budget. They will facilitate technical architecture decisions, manage complex installations, and maintain effective relationships with stakeholders and customers.
You will serve as a forward-deployed technical liaison to deploy, manage, and validate large-scale AI Compute and HPC infrastructure for enterprise customers. This role involves collaborating with internal teams and partners to define project requirements, provide technical support, and perform knowledge transfers.
You will serve as a technical SME to design developer tools, APIs, and workflows for chemistry and materials science. You will also collaborate across research and engineering teams to shape the NVIDIA ALCHEMI software stack and represent the company at scientific conferences.
The researcher will identify hardware vulnerabilities on SoC and GPU designs and develop advanced security tools and techniques. They will also guide the integration of security mitigations and conduct research into side-channel, fault, and physical attacks.
Lead joint solution development with Global System Integrators to integrate NVIDIA AI technology into healthcare and life sciences offerings. Develop and execute strategic go-to-market plans to drive revenue growth and accelerate AI adoption across the sector.
Senior Software Engineer - Accelerated Kubernetes Runtime Team
NVIDIA
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Full Time
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3 months ago
NVIDIA
Design and implement automation systems to orchestrate the lifecycle of runtime components across thousands of Kubernetes clusters. Develop Kubernetes controllers, operators, and CRDs to manage the installation, upgrade, and validation of accelerated compute components.
The Client Director will drive business relationships with Global System Integrators in EMEA to promote AI-enabled services and GPU-accelerated computing. They will act as a bridge between partners and NVIDIA teams to execute joint go-to-market plans, manage PoCs, and support technical enablement.
Maintain large scale computational and AI infrastructure, focusing on monitoring, logging, and workload orchestration. Serve as a key technical resource, developing and documenting standard methodologies and operational guidelines.
Primary responsibilities include building and operating AI/HPC infrastructure for new and existing customers. The role involves supporting operational and reliability aspects of large-scale AI clusters.
Senior Systems Software Engineer, Data Center Infrastructure Management - EngOps
NVIDIA
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Full Time
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4 months ago
NVIDIA
The engineer will take ownership of daily cluster failures and issues, troubleshooting them promptly to maintain optimal cluster availability and performance. Responsibilities also include managing updates to site controller management nodes and overseeing the rollout and rollback of cluster software and firmware updates.
This role involves serving as a trusted technical advisor and champion for the EMEA AI Natives developer ecosystem, driving adoption of NVIDIA technologies by demonstrating groundbreaking solutions and accelerating critical workloads. The manager will also guide partners and startups through integration, track ecosystem growth, and collaborate cross-functionally to optimize adoption strategies.
This role involves defining and driving the product vision, strategy, and roadmap for source control systems essential for large-scale chip and software development, focusing on performance, reliability, and scalability. The manager will also own the evolution of repository architecture, optimize developer workflows in partnership with engineering teams, and establish metrics to measure impact.
This role involves researching and developing techniques to optimize key Cloud and HPC CPU workloads specifically on NVIDIA's CPU, requiring in-depth analysis for current and future generations. Responsibilities also include engaging with the developer community, guiding framework developers, and contributing directly to their software stack or developing reference code.
The engineer will develop and implement CUDA Core Libraries in C++ and/or Python, focusing on parallel algorithms and idiomatic language bindings for core CUDA functionality. Responsibilities also include composing, optimizing, and evolving GPU algorithms and APIs, owning features end-to-end, and improving the overall developer experience.
The Senior DFT Engineer will define and implement SCAN, MBIST, and JTAG debug structures, driving post-silicon testing plans and creating ATPG and MBIST test vectors. They will also build DFT timing constraints, partner with physical design teams, and work with the post-silicon team to bring up test patterns on actual silicon.
Primary responsibilities involve deploying, managing, and maintaining AI/HPC infrastructure in Linux-based environments for customers, acting as the domain expert during planning and implementation phases. This role also requires creating handover documentation, performing knowledge transfers, and providing feedback to internal teams regarding bugs and improvements.
Senior Networking Solution Test Engineer – AI Cluster Debugging
NVIDIA
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Full Time
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4 months ago
NVIDIA
The role involves designing and reviewing test requirements for NVLink, Ethernet, and InfiniBand components within large-scale AI clusters, and building realistic customer-like testbeds incorporating heterogeneous hardware and complex network fabrics. Responsibilities also include owning end-to-end cluster troubleshooting, reproducing customer scenarios, triaging issues across the stack, and driving them to root cause resolution.
The role involves developing a highly optimized inference framework that runs on the world’s largest supercomputers and data centers, focusing on performance and scalability in AI networking acceleration.
The role involves leading and cultivating relationships with strategic Venture Capital firms and their portfolio companies across the EMEA region to amplify NVIDIA's influence in the startup ecosystem. This includes enabling successful partnerships between portfolio companies and NVIDIA business units and planning executive engagement opportunities.
This role focuses on redefining AI hardware development methodology by inventing next-wave techniques, pioneering AI-driven automation for sophisticated ASIC conception, exploration, and closure. Responsibilities include taking a comprehensive view of the ASIC lifecycle to identify bottlenecks where automation and AI can improve convergence and turnaround time.
The engineer will take a comprehensive view of the ASIC development lifecycle to identify bottlenecks where automation and AI can improve predictability and turnaround time. They will also establish quantitative metrics to measure efficiency and serve as a technical catalyst by sharing best practices and mentoring engineers on emerging AI-enabled techniques.
EMEA Sales Senior Account Manager, Smart Spaces and Local Government
NVIDIA
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Full Time
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5 months ago
NVIDIA
This role involves owning strategic relationships with leading cities and public-sector organizations to position NVIDIA's platforms and AI Factory strategy for modernizing public services and competitiveness across EMEA. Key activities include crafting revenue growth for Smart Cities solutions, building a robust pipeline focused on AI deployment, and developing long-term relationships with senior city leaders.
As a Senior Formal Verification Engineer, you will verify ASICs using formal verification tools and define the verification scope to ensure correctness. You will collaborate with various teams to resolve design issues and improve verification methodologies.
As a key member of the ASIC Verification team, you will verify the design and implementation of the inference accelerator. You will collaborate with architects, designers, and verification teams to ensure the correctness of the design.
As a key member of the Design team, you will implement, document and deliver high performance, area and power efficient RTL. You will collaborate with various teams to analyze architectural trade-offs and deliver fully verified designs.
As a Senior Formal Verification Engineer, you will verify ASICs using formal verification tools and define the verification scope to ensure correctness. You will collaborate with various teams to improve methodologies and deliver high-quality results on schedule.
Analyze Deep Learning models and investigate TensorRT stability and performance issues. Work with an internationally distributed team for CUDA and TensorRT development.
Lead architecture for cloud-networking and security solutions while designing state-of-the-art system architecture for DPUs & NICs technologies. Collaborate with global teams to innovate and develop proof of concept prototypes into full-fledged products.
Responsible for NVIDIA board team product management, including product yield management and ensuring product engineering implementation. Supervise NVIDIA board products’ quality and yield goals, and take corrective actions if needed.
The Solutions Architect will work with customers on data center GPU server and networking infrastructure deployments, guiding discussions on network topologies and supporting server/network/cluster deployments. They will also identify new project opportunities and build custom product demonstrations for solutions addressing critical business needs.
Collaborate with internal and external teams to define system requirements for fault-tolerant quantum computing. Develop novel approaches to quantum error correction and calibration supported by rigorous systems analysis.
Contributing to the development of CUDA Quantum by building core infrastructure for inter-device communication and efficient execution across multiple processors. Partnering with architects and product managers to create an extensible toolchain integrating quantum architecture specific components.
Develop automation for deploying Kubernetes clusters for streaming media use cases and monitor and manage these clusters. Collaborate with other NVIDIA R&D teams globally in a fast-paced environment.
Senior Systems Software Security Engineer – Data Center Systems
NVIDIA
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Full Time
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9 months ago
NVIDIA
You will focus on securing NVIDIA’s Data Center Systems by delivering necessary security features and engaging with teams to drive implementation. Your role will involve designing and developing optimized security solutions following industry standards.
