Cloud Application Architect jobs

What you’ll be doing:

• Understand, analyze, profile, and optimize AI training workloads on state-of-the-art hardware and software platforms.

• Guide development of future generations of artificial intelligence accelerators and systems.

• Develop detailed performance models and simulator infrastructure for computing systems accelerating AI training, and implement and evaluate hardware feature proposals.

• Collaborate across the company to guide the direction of machine learning at NVIDIA; spanning teams from hardware to software and research to production.

• Drive HW/SW co-design of NVIDIA’s full deep learning platform stack, from silicon to DL frameworks.

What we need to see:

• PhD in CS, EE or CSEE and 3+ years; or MS (or equivalent experience) and 6+ years of relevant work experience.

• Strong background in computer architecture, with a proven track record of architecting features in shipping high-performance processors.

• Background in artificial intelligence and large language models, in particular training algorithms and workloads.

• Experience analyzing and tuning application performance on state-of-the-art hardware.

• Experience with processor and system-level performance modelling, simulation, and evaluation before silicon exists.

• Programming skills in C++ and Python.

• Familiarity with GPU computing across all layers of the AI stack, from DL frameworks like PyTorch down to CUDA.

What you'll be doing:

• You will be contributing to power estimation models and tools for GPU products and systems like NVIDIA DGX.

• Early GPU & System Architecture exploration with focus on energy efficiency and TCO improvements at GPU and Datacenter level.

• You will help with Performance vs Power Analysis for NVIDIA future product lineup.

• Deploy machine learning techniques to develop highly accurate power and performance models of our GPUs, CPUs, Switches, and platforms.

• Understand the workload characteristics for GenAI/HPC workloads at Datacenter Scale (multi-GPU) to drive new HW/SW features for Perf@Watt improvements.

• Modeling & analysis of cutting-edge technologies like high speed & high-density interconnects.

What we need to see:

• Pursuing a MSEE/MSCE, or equivalent experience related to Power / Performance estimation and optimization techniques.

• Knowledge of energy efficient chip design fundamentals and related tradeoffs.

• Familiarity with low power design techniques such as multi-VT, Clock gating, Power gating, and Dynamic Voltage-Frequency Scaling (DVFS).

• Understanding of processors (GPU is a plus), system-SW architectures, and their performance/power modeling techniques.

• Proficiency with Python and data analysis packages like: Pandas, NumPy, PyTorch.

• Familiarity with performance monitors/simulators used in modern processor architectures.

What you’ll be doing:

• Working with Cloud Service Providers to develop and demonstrate solutions based on NVIDIA’s groundbreaking software and hardware technologies.

• Build and deploy solutions at scale using NVIDIA's AI software on cloud-based GPU platforms.

• Build custom PoCs for solutions that address customer's critical business needs while applying NVIDIA's hardware and software technologies.

• Partner with Sales Account Managers or Developer Relations Managers to identify and secure business opportunities for NVIDIA products and solutions.

• Conduct regular technical customer meetings for project/product details, feature discussions, intro to new technologies, and debugging sessions.

• Prepare and deliver technical content to customers including presentations about purpose-built solutions, workshops about NVIDIA products and solutions, etc.

What we need to see:

• BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience.

• 7+ years of Solutions Engineering (or similar Sales Engineering roles) experience.

• Established track record of deploying AI/ ML solutions in cloud environments including AWS, GCP, Azure or OCI

• Knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes, data center deployments, etc.

• Effective time management and capable of balancing multiple tasks.

• Ability to communicate ideas clearly through documents, presentation, etc.

Ways to stand out from the crowd:

• AWS, GCP, Azure or OCI Professional Solution Architect Certifications

• Hands-on experience with NVIDIA GPUs and SDKs (i.e. CUDA, Triton, TensorRT-LLM, etc.)

• Deep understanding of the full software development lifecycle, including best practices for system design, architectural patterns, and comprehensive testing.

• Solid working knowledge of Python

• System-level experience, specifically GPU-based systems

NVIDIA is seeking a Senior Technical Program Manager to lead the Infrastructure and Product Security and Compliance program for DGX Cloud. In this role, you will ensure our platforms and partner ecosystem meet the highest standards of trust, resilience, and governance.

As a Senior TPM focused on Cloud Security, you will own the design and execution of a DGXC-wide infrastructure security program that strengthens how DGXC operates with Cloud Service Providers (CSPs) and NVIDIA Cloud Partners (NCPs). You will drive security initiatives by embedding compliance controls, governance frameworks, and best practices across infrastructure, platform, and product teams. This role also ensures Product Security is integrated into product roadmap planning and the software development lifecycle, aligning product and infrastructure priorities. You will work closely with senior leaders and cross-functional teams in Security, Compliance, DevOps, and Engineering to continuously enhance and scale the DGX Cloud Security Posture.

What You’ll Be Doing:

• Lead alignment across engineering, product, security, and partner teams to deliver against cloud security guidelines with CSP and NCP partners.

• Drive programs that strengthen vulnerability management, access control, patching, and compliance readiness for SOC 2, ISO 27001, and related certifications.

• Operate DGXC-wide security engineering forums and processes, establishing security KPIs, dashboards, and “run safe” SRE practices.

• Partner with the CISO organization to define and assess emerging cloud providers against DGX Cloud security requirements, driving measurable improvements and action plans.

• Implement and evolve security controls frameworks (e.g., SSH hardening, IAM, secret rotation) in CI/CD pipelines to ensure continuous compliance.

• Lead certification readiness and audit cycles, including SOC 2 Type 1 & 2 and ISO 27001, from control mapping through evidence collection and remediation.

• Chair the DGX Cloud Security & Compliance Working Group, managing governance reviews, risk dashboards, and executive reporting on posture and metrics.

• Develop training programs to build security and compliance awareness across Product, DevOps, and Engineering teams.

• Create playbooks and automation frameworks that streamline certification renewals, patching cycles, and vulnerability management workflows.

• Maintain and continuously improve technical compliance documentation, including system diagrams, process flows, and control mappings.

What We Need to See:

• 12+ years of Program Management experience driving the planning and execution of large programs, software engineering projects in a fast paced environment.

• Consistent track record delivering successful Security, Risk, and/or Compliance programs, particularly in cloud IaaS and SaaS environments, resulting in full certification of a suite of products and services.

• Experience leading efforts related to SOC2 (Type 1 and Type 2) audits and readiness, including leading control implementation (e.g., access controls, change management, vulnerability management).

• Experience operationalizing vulnerability management, patch management, SSH key governance, and access controls across distributed systems.

• Ability to think strategically and tactically and to build consensus in making programs successful; ability to resolve technical issues and resource constraints across cross-functional teams.

• Demonstrated ability to define metrics, dashboards, and risk indicators that measure posture improvement and audit readiness.

• Proficiency with tools like JIRA, to comfortably guide engineering teams on execution in an Agile/scrum manner and ensure accurate governance artifacts are delivered.

• Excellent executive communication and presentation skills able to distill complex technical and compliance topics for senior leadership

• MS EE or CS degree, or equivalent experience.

Ways to Stand Out from the Crowd:

• Highly motivated with strong interpersonal skills, with proven track record to work successfully with multi-functional teams and coordinate effectively across organizational boundaries and geographies.

• Experience implementing security features in a multi-cloud environment.

• Experience with sophisticated compliance programs, such as FedRamp, SCO2, or ISO certification efforts.

• Solid understanding of tier 1 cloud technologies (AWS, GCP, Azure, OCI).

• Experience with productivity tools and process automation.

What you’ll be doing:

• Develop and test sample applications for chemistry and materials discovery using artificial intelligence.

• Help develop AI first workflows using NVIDIA technology and popular deep learning frameworks.

• Create clear, practical examples and documentation for developers and researchers.

What we need to see:

• Pursuing a PhD in Chemistry, Materials Science, Computer Science, or a related field.

• Familiarity with AI/ML concepts and experience with at least one deep learning framework (e.g., PyTorch, TensorFlow).

• Basic understanding of chemistry or materials science principles.

Ways to stand out from the crowd:

• Experience with GPU programming or CUDA and machine learning frameworks such as PyTorch.

• Contributions to open-source projects related to AI or scientific computing.

• Coursework or projects involving AI for scientific applications.

You will also be eligible for Intern

What you'll be doing:

• Working with NVIDIA AI Native customers on data center GPU server and networking infrastructure deployments.

• Guiding customer discussions on network topologies, compute/storage, and supporting the bring-up ofserver/network/clusterdeployments.

• Identifying new project opportunities for NVIDIA products and technology solutions in data center and AI applications.

• Conducting regular technical meetings with customers as a trusted advisor, discussing product roadmaps, cluster debugging, and new technology introductions.

• Building custom demonstrations and proofs of concept to address critical business needs.

• Analyzing and debugging compute/network performance issues.

What we need to see:

• BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or related fields, or equivalent experience.

• 5+ years of experience in Solution Engineering or similar roles.

• System-level understanding of server architecture, NICs, Linux, system software, and kernel drivers.

• Practical knowledge of networking - switching & routing for Ethernet/Infiniband, and data center infrastructure (power/cooling).

• Familiarity with DevOps/MLOps technologies such as Docker/containers and Kubernetes.

• Effective time management and ability to balance multiple tasks.

• Excellent communication skills for articulating ideas and code clearly through documents and presentations.

Ways to stand out from the crowd:

• External customer-facing skills and experience.

• Experience with the bring-up and deployment of large clusters.

• Proficiency in systems engineering, coding, and debugging, including C/C++, Linux kernel, and drivers.

• Hands-on experience with NVIDIA systems/SDKs (e.g., CUDA), NVIDIA networking technologies (e.g., DPU or equivalent experience, RoCE, InfiniBand), and/or ARM CPU solutions.

• Familiarity with virtualization technology concepts.