The Senior Sales Account Manager will drive growth and develop new markets within the UK Financial Services Industry by building strategic partnerships and customer value. They will orchestrate resources to deliver impactful technology solutions and serve as the primary hub for the local FSI ecosystem.
The Strategy Analyst will support leadership by developing and executing core sales strategies and unifying planning across global field marketing. They will work cross-functionally with Enterprise Marketing, Sales Operations, and Finance to implement effective reporting and feedback mechanisms.
Drive market growth by building and implementing strategies for NVIDIA AI and accelerated computing solutions within the telecommunications sector. Foster strong executive relationships and identify new business opportunities to position NVIDIA as a strategic partner for network transformation.
Lead the EMEA segment sales team to drive product sales and implement effective market penetration strategies. Collaborate with cross-functional teams to analyze market trends and provide actionable insights for strategic growth.
Manage and develop relationships with Cloud partners across the EMEA region to drive revenue and business execution. Maintain a rolling pipeline of opportunities, track partner training compliance, and advocate for NVIDIA solutions within the partner ecosystem.
The role involves leading the EMEA go-to-market strategy for NVIDIA's Agentic AI Platform across diverse enterprise and regulated sectors. You will collaborate with cross-functional teams to drive adoption of AI technologies, refine sales toolkits, and provide expert guidance on model licensing and security.
Lead the EMEA go-to-market strategy across NVIDIA AI Enterprise, Run:ai, Physical AI, and vGPU portfolios. Manage customer success operations, including onboarding, renewals, and executive stakeholder reviews to drive commercial results.
Engage with AI-native startups and scaleups to understand their business needs and deliver high-value NVIDIA AI solutions. Lead cross-functional teams to drive demand, build customer references, and represent NVIDIA within the AI ecosystem.
You will act as a technical advisor to partners, enabling them with NVIDIA's accelerated computing solutions including AI, hybrid cloud, and digital twins. This involves delivering technical presentations, workshops, and proof-of-concepts to drive partner success and go-to-market strategies.
The Senior Sales Customer Success Manager will integrate customers by assisting with license registration and initial value planning while aligning workloads with NVIDIA software capabilities. They will also coordinate cross-functional teams to remove adoption blockers and lead executive reviews to connect technical adoption to business outcomes.
You will architect and deploy AI-powered validation pipelines to enhance the efficiency and scalability of semiconductor design toolchains. Additionally, you will collaborate with cross-functional teams to integrate AI solutions that eliminate friction and drive continuous improvement across silicon development workflows.
The role involves providing direct program support to leadership by coordinating priorities, tracking key initiatives, and ensuring alignment with strategic objectives. It also focuses on improving business operations through process optimization, cross-functional tasking, and maintaining clear communication across core business units.
You will design and build agentic AI solutions and tools to automate workflows for the NVIS delivery organization. This involves integrating LLMs with internal systems and data pipelines to improve project visibility and operational efficiency.
You will lead and develop a distributed team of security and infrastructure engineers to build scalable security solutions for a massive GPU fleet. The role involves setting technical strategy, fostering a culture of operational excellence, and communicating complex risk profiles to executive leadership.
You will architect and build foundational security primitives and automated guardrails to protect large-scale AI infrastructure. The role involves designing production-grade security services and integrating them into the CI/CD pipeline to ensure platform integrity.
The role involves deploying, managing, and validating large-scale AI Compute and HPC infrastructure in Linux environments for enterprise customers. You will act as a technical liaison between NVIDIA, partners, and customers to ensure successful system implementation and optimization.
Design and build advanced evaluation environments for frontier deep learning models, including LLMs and agentic systems. Develop novel methodologies to assess model performance and translate evaluation signals into actionable decisions for research and product teams.
The Logistics Execution Program Manager will lead end-to-end logistics workflows, overseeing operational programs and partner performance to ensure reliable delivery. They will drive continuous improvement initiatives and manage capacity planning to support rapid growth and product launches.
The Program Manager will oversee BriefingSource administration, Salesforce reporting, and the development of AI-enabled workflows to support global EBC operations. They will partner with sales and operations teams to define metrics, ensure data quality, and drive strategic alignment across the program.
You will serve as a technical advisor to R&D teams, helping them integrate NVIDIA accelerated computing and AI into materials discovery and chemical process workflows. Additionally, you will collaborate with sales and business development teams to drive ecosystem success across materials science and chemistry accounts.
You will build and maintain a system that gathers, aggregates, and normalizes topology data to support provisioning systems and workload schedulers. Additionally, you will contribute to the open-source Topograph project and interface with NVIDIA hardware to optimize GPU communication for large-scale workloads.
The Technical Program Manager will own end-to-end deployment readiness for new rack-scale AI platforms, ensuring alignment across internal engineering teams and OEM partners. They will drive the execution of deployment plans, manage risks, and implement quality assurance processes to ensure successful mass production rollouts.
The Solutions Architect will design and scale high-performance AI infrastructure for customers while providing technical support for GPU and networking products. They will also manage the product lifecycle and foster technical relationships with key customer accounts.
You will lead SMT process activities and supplier quality management in the Southeast Asia region to ensure adherence to NVIDIA's reliability and performance standards. This involves driving process improvements, managing NPI and mass production builds, and collaborating with cross-functional teams to optimize PCBA manufacturability.
Lead end-to-end project delivery for enterprise data center environments, managing the full lifecycle from strategic alignment to production handover. Facilitate technical discussions, drive solution design, and maintain strong relationships with global internal teams and customers.
The Senior Program Manager will oversee material readiness, build schedules, and communicate status updates to headquarters. They will also lead mass production meetings and drive process improvements across procurement, planning, manufacturing, and engineering teams.
You will lead the delivery of agentic AI systems to automate security operations, including detection, investigation, and response workflows. You will also provide technical direction for complex AI initiatives and drive them from experimentation through to production deployment.
Develop advanced algorithms for computational geometry, mesh generation, and discretization to improve simulation performance and accuracy. Collaborate with cross-functional teams to integrate these methods into engineering workflows for digital twins and autonomous systems.
You will build, deploy, and tune security detections across various platforms to identify and investigate insider threats. Additionally, you will lead investigations into unusual data movement and anomalies while developing automation tools to improve efficiency.
The role involves building and maintaining large-scale AI/HPC networking infrastructure for customers. Responsibilities include managing the full service lifecycle, ensuring system performance, and providing technical support.
You will be responsible for strategy creation, sales account management, and driving revenue growth for enterprise customers like Walmart and Sam's Club. This involves building strategic partnerships, executing go-to-market plans, and evangelizing NVIDIA's platform and technologies.
Analyze and improve the performance of High Performance Computing (HPC) applications by driving compiler optimizations and library enhancements. Collaborate with compiler development and application engineering teams to deliver effective solutions across CPU and GPU platforms.
Analyze High Performance Computing (HPC) applications to identify performance characteristics and optimization opportunities. Collaborate with compiler and application engineering teams to accelerate GPU-based HPC workloads.
Drive technical innovation by developing kernel generation and computational graph optimizations for next-generation GPUs. Collaborate with hardware and software teams to architect future silicon and scale AI workloads for the datacenter.
You will design, build, and tune high-confidence security detections across various platforms to identify and mitigate threats. Additionally, you will drive the full detection lifecycle, including validation, documentation, and collaboration with incident response teams to improve detection efficacy.
The Senior Account Manager will develop and execute strategic growth plans for NVIDIA's consumer and edge products with AIC and OEM partners in Thailand. This role involves managing partner relationships, driving revenue performance, and leading go-to-market strategies across gaming, AI PC, and workstation segments.
Analyze end-to-end performance of large-scale AI workloads across compute, network, storage, and software stacks. Design and execute performance studies to establish baselines, diagnose bottlenecks, and drive optimizations from investigation through deployment.
Design and implement GPU-native numerical methods to enhance engineering simulation performance and reliability across NVIDIA platforms. Collaborate with research and engineering teams to transition innovative prototypes into production-grade software capabilities.
Design, build, and maintain infrastructure services while managing the software lifecycle to meet business objectives. Participate in on-call rotations, incident response, and the definition of service level objectives to ensure system reliability.
The Solutions Architect will design and operationalize NVIDIA's hardware and software solutions, focusing on datacentre power, cooling, and MEP integration. They will serve as the primary technical contact for customers, guiding them through the full lifecycle of large-scale GPU cloud infrastructure deployments.
The Senior Account Manager will lead business development and strategic engagement with a major Silicon Valley account to drive networking and AI solution sales. They will act as the primary liaison between the customer and internal technical teams to manage forecasts, supply, and product roadmap requirements.
You will lead and expand designated sales accounts in Southeast Asia while formulating strategies to drive revenue and customer success. Additionally, you will coordinate infrastructure planning and deployment with cross-functional teams to grow the regional AI ecosystem.
You will drive customer issues with networking adapter and DPU deployments from inception to resolution while developing features and tools for enterprise service offerings. Additionally, you will collaborate with engineering teams to improve the reliability and performance of NVIDIA networking products.
The Engineering Manager will lead a team to build and scale a customer delivery and self-service function for Kubernetes clusters. They will transform manual processes into automated workflows while partnering with cross-functional teams to ensure efficient platform enablement and production acceptance.
You will lead the technical strategy and architecture for DGX Cloud full stack integration, focusing on the interface between hardware, firmware, and system software. This role involves collaborating cross-functionally to deliver scalable, secure, and high-performance accelerated computing solutions across diverse datacenter environments.
Design, implement, and maintain large-scale HPC/AI clusters while managing job scheduling and orchestration tools. Develop automation tooling for infrastructure deployment, monitoring, and continuous integration pipelines.
You will design, build, and optimize GPU-accelerated software for deep learning inference frameworks like SGLang and vLLM. Your work involves performance tuning of LLM and Generative AI models across various NVIDIA hardware architectures.
You will serve as a technical advisor to engineering software developers, helping them integrate NVIDIA's accelerated computing, Omniverse, and physics-ML into their simulation pipelines. Additionally, you will partner with sales and business development teams to drive ecosystem success across industrial engineering accounts.
Lead a team of solutions architects and engineers to design, debug, and deploy AI hardware and software technologies in customer data centers. Act as a senior technical point of contact while partnering with product and sales teams to influence product roadmaps and ensure high-quality delivery.
You will design, architect, and implement complex Ethernet networking solutions for data centers while providing technical expertise to support AI and accelerated computing workloads. Additionally, you will develop network automation scripts and collaborate with internal teams to improve product strategy and customer deployment outcomes.
Lead a team of solutions architects and engineers to design, debug, and deploy large-scale AI hardware and software solutions in customer data centers. Act as a senior technical point of contact to influence product roadmaps and ensure high-quality delivery for strategic AI lab customers.
Define end-to-end reference architectures integrating GPU and networking technologies for strategic customers. Support sales teams by identifying business opportunities, conducting technical account management, and delivering product demonstrations.
The Factory Planner is responsible for translating demand into executable factory plans by aligning materials, capacity, and manufacturing readiness across partners. They will utilize AI-enabled analytics and automation tools to drive build commits, monitor execution, and improve overall planning efficiency.
You will be responsible for strategy creation, sales account management, and driving revenue growth for Walmart and Sam's Club. This role involves building strategic partnerships and evangelizing NVIDIA's platform and technologies to key stakeholders.
Lead developer relations for quantum computing across federal research programs by driving adoption of NVIDIA's quantum SDKs. Act as a technical bridge between mission scientists and NVIDIA's engineering teams to solve high-impact research problems.
You will design and scale deep learning infrastructure libraries to support autonomous vehicle training on massive GPU clusters. This involves optimizing training pipelines, improving data loader efficiency, and collaborating with research teams to enhance model experimentation.
You will be responsible for defining and implementing chip pad rings, substrate interconnect schemes, and leading the package layout design process. This role involves collaborating with cross-functional teams including circuit, signal integrity, RTL, and system design engineers to ensure robust electrical package performance.
You will act as a trusted technical advisor to help customers design, deploy, and optimize large-scale AI training and inference infrastructure. Additionally, you will analyze performance data to identify system bottlenecks and collaborate with internal teams to drive product health.
Lead the architecture, design, and operation of NVIDIA's global backbone network to support high-capacity AI-training infrastructure. Automate network infrastructure end-to-end, including circuit provisioning, capacity management, and failure detection.
Provide onsite technical support for large-scale NVIDIA AI datacenter deployments and resolve complex hardware issues. Establish strong technical relationships with customer architects and provide training to sales teams and partners.
Build and operate core infrastructure services that power global AI infrastructure and DGX Cloud deployments. Develop scalable cloud-native platform services and automate infrastructure provisioning and lifecycle management.
You will profile, benchmark, and analyze AI and HPC workloads on GPU and CPU clusters to identify performance bottlenecks. Additionally, you will collaborate with cross-functional teams to develop diagnostic tools and provide actionable performance insights.
Drive growth in the Cisco EMEA channel business through partner development, enablement, and the execution of strategic business initiatives. Collaborate with Cisco channel teams and partners to accelerate pipeline creation and improve market execution for NVIDIA platforms.
Develop and execute a technical strategy to drive the adoption of NVIDIA GPU platforms and AI solutions among startups and software partners in Southern Europe. Act as a technical mentor and evangelist to engage developer communities and influence technical leaders across key industries.
The engineer will perform hardware and software verification and validation to ensure product quality and stability. They will also troubleshoot testing procedures, optimize production jigs, and provide detailed activity reports.
You will serve as a technical advisor and champion for the EMEA AI developer ecosystem to drive the adoption of NVIDIA technologies. This involves collaborating with engineering and product teams to accelerate workloads, provide technical enablement resources, and influence product roadmaps based on partner feedback.
Drive the integration of NVIDIA's software libraries, models, and frameworks across strategic partners like Google Cloud and DeepMind. Lead cross-functional teams to accelerate critical workloads and influence partner product roadmaps through technical advocacy.
You will serve as a technical advisor and champion for the EMEA AI developer ecosystem to drive the adoption of NVIDIA technologies. This involves collaborating with internal teams and partners to accelerate workloads, provide technical enablement, and influence product roadmaps based on field insights.
You will support the creation, implementation, and verification of AI factories by running and debugging AI/LLM workloads on Linux-based GPU clusters. Additionally, you will collaborate with cross-functional teams to optimize performance, scalability, and observability for customer-ready AI environments.
You will lead strategic customer initiatives by partnering with engineering and product teams to accelerate AI workload deployment within the Amazon ecosystem. Additionally, you will serve as a trusted business advisor to influence partnership direction and drive measurable business outcomes through deep technical and market expertise.
The role involves bridging cutting-edge AI research with production-grade infrastructure by identifying, prototyping, and integrating agentic system methods. You will also design evaluation harnesses and secure workflows to ensure agent reliability and safety in enterprise environments.
The role involves designing and optimizing large-scale AI infrastructure while collaborating with customers to maximize GPU utilization and workload throughput. You will also profile distributed training and inference workloads to identify bottlenecks and lead technical engagements for high-performance AI systems.
Develop and manage automation software for NVIDIA's GPU Cloud and SuperPod deployments to enable efficient network design and lifecycle management. Collaborate with infrastructure experts to build scalable, zero-touch deployment solutions and integrate with various service APIs.
Drive revenue growth and achieve quota attainment for NVIDIA's networking portfolio across Enterprise accounts. Lead customer-facing discussions to position networking solutions within broader AI and data center initiatives while collaborating with technical teams.
You will develop and execute a strategy for the healthcare robotics developer ecosystem, focusing on spatial intelligence and simulation workflows. Additionally, you will engage with MedTech partners and developers to provide technical guidance, create educational content, and represent the developer voice within NVIDIA.
Lead and coach a team of Storage Production Engineers to design, deploy, and maintain large-scale, high-performance storage systems. Partner with engineering and AI/ML teams to optimize data pipelines, ensure system reliability, and drive operational excellence.
The role involves partnering with internal customers to ensure successful adoption of DGX Cloud, removing technical blockers, and optimizing workload performance. You will translate complex business and technical requirements into scalable infrastructure recommendations while driving product improvements through customer insights.
Drive NVIDIA platform adoption by nurturing strategic partnerships with CAE developers and ISVs while providing technical expertise. Inform product strategy by representing the developer community and leading technical collaborations across internal teams.
Drive NVIDIA platform adoption by nurturing strategic partnerships with CAE developers and ISVs. Inform product strategy by representing the developer community and identifying high-impact technical solutions.
You will scout, recruit, and support AI startups in the public sector, energy, and CAE industries to join the NVIDIA Inception program. Additionally, you will collaborate with cross-functional teams to drive go-to-market initiatives and accelerate the adoption of NVIDIA solutions.
The Solution Architect will partner with government clients to translate mission goals into AI-enabled strategies and deploy technical solutions. They will also mentor partners and customers while building resources to support the adoption of NVIDIA's AI software and hardware technologies.
Provide hands-on technical mentorship to customers on the NVIDIA GenAI stack and guide the development of Agentic AI workflows. Build demonstrations and POCs while partnering with engineering and sales teams to secure design wins.
Lead strategic relationships with cities and public-sector organizations to drive the adoption of NVIDIA's AI platforms and Digital Twin technology. Focus on crafting revenue growth and developing AI factories to modernize public services and urban infrastructure.
Coordinate incident response, maintenance, and reporting across NVIDIA's datacenter portfolio to ensure reliability and minimize service disruptions. Lead root cause analysis and develop reliability standards, automation, and health scores to predict and isolate points of failure.
Lead the design, implementation, and validation of high-performance data center networks for strategic customers using the PDI framework. Provide technical expertise in Ethernet routing and automation to optimize GPU-enabled AI applications and server infrastructure.
Design and implement innovations for managing GPU-based AI servers, focusing on BMC firmware and OOB management. Collaborate with global teams, hardware engineers, and industry partners to deliver high-end enterprise server platforms.
The role involves productizing new GPU boards for datacenter architectures and optimizing production lines for HGX GPU Accelerated Server Platforms. Responsibilities include developing diagnostic tests, ensuring DFx compliance, and collaborating with contract manufacturers to optimize assembly and yield.
Serve as a technical advisor to security companies to drive the adoption of NVIDIA's software stack for AI and Agentic environments. Collaborate with internal engineering and product teams to influence roadmaps based on developer feedback and ecosystem trends.
Lead the architecture for cloud-networking, security, and orchestration solutions for DPUs and NICs. Develop end-to-end solutions from the application level to hardware and create reliable architecture specifications.
Own the mechanical aspects of production test fixtures, jigs, and enclosures while overseeing maintenance and calibration across global contract manufacturing sites. Support NPI mechanical readiness and provide technical guidance to ensure production quality and manufacturing excellence.
Analyze HPC applications to improve performance by driving compiler optimizations and library enhancements. Evaluate the impact of NVHPC components and port applications across different platforms and programming models.
The role involves connecting with Media and Entertainment customers to identify business needs and quantify market opportunities. The manager will orchestrate resources to implement partnership strategies and drive the adoption of NVIDIA technology solutions.
Responsible for product engineering of NVIDIA adaptors, switches, and interconnect products. This includes establishing and training CM engineering teams and collaborating with cross-functional teams to resolve bugs and improve product quality.
Design and deploy GPU-accelerated AI solutions and industrial digital twins for energy operations across power generation, grid, and oil & gas sectors. Act as a technical advisor to integrate NVIDIA platforms into control rooms and field environments to solve last-mile deployment challenges.
Lead NVIDIA's engagement with the French automotive ecosystem by building C-level relationships across OEMs and Tier-1 suppliers. Develop multi-year account strategies to drive the adoption of NVIDIA's AI hardware and software platforms.
Create and deliver technical content, tutorials, and workshops to educate the developer community on the CUDA platform. Collaborate with product and engineering teams to provide developer-centric insights and inform the product roadmap.
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.
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.
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.
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 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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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.
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.
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.
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.
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.
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.
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.
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 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.
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.
