NVIDIA

Blockchain Engineer

• Contribute to the DGX Cloud team responsible for production systems enabling large-scale GPU clusters for AI workloads
• Develop custom software for scheduling GPU resources on Kubernetes
• Implement monitoring and health-management capabilities for reliability, availability, and scalability of GPU assets
• Harness data streams from GPU hardware diagnostics, cluster telemetry, and network telemetry
• Collaborate with teams across NVIDIA to ensure production AI clusters run reliably, consistently, and with maximum performance
• Evaluate system failures and improve services through a defined incident-management process

Principal Software Engineer, Distributed Systems Engineer – DGX Cloud

Data Engineer

• Define requirements and acceptance criteria for the platform's flagship products: single-source-of-truth tables for clusters, associated components, customers, and workloads, along with relationship tables
• Partner with source and collector teams across DGX Cloud to onboard data and define versioned data contracts covering schema, semantics, freshness, quality, and change notification
• Drive identifier and schema standardization upstream with producing teams, recording, owning, and tracking each standardization decision to closure
• Work with infrastructure security, compliance, and enterprise data teams to define the security model
• Engage with engineering leadership to establish priorities and resource allocation, sequence delivery against firm external constraints, and gain prioritization consensus across collaborating teams
• Define and report measures including standardization debt per source, pipeline freshness and quality SLOs, source onboarding throughput, and time to first answer for a new consumer
• Define requirements and build the case for extending the platform to NVIDIA Cloud Partners and cloud service providers

Senior Data Platform and Analytics Product Manager – DGX Cloud

Backend Engineer

• Build Go controllers and APIs to install, upgrade, and validate GPU cluster software
• Integrate components, define API contracts, and evolve Helm and Argo CD delivery toward controller-driven automation
• Build validation pipelines that inform release decisions across providers and GPU platforms
• Develop systems to allocate GPU capacity across validation runs and account for cloud reservations and quotas
• Improve qualification efficiency through reusable tests and clear failure reports
• Bring new providers and GPU hardware into production
• Resolve integration failures with partner teams
• Turn initial provisioning, upgrade, and operational checks into repeatable automation
• Collaborate across Runtime, Release Engineering, and Provider Integration teams
• Influence what reaches production across NVIDIA's GPU cloud infrastructure

Senior Software Engineer, Kubernetes Runtime

Production Engineer

• Build automation for bare-metal provisioning, hardware validation, firmware and software upgrades, repair, and cluster lifecycle management
• Develop tools that interact with BMC and Redfish interfaces to monitor hardware health, manage server state, and assist recovery workflows
• Handle and advance NVIDIA NVL72 systems and BlueField-3 or later DPUs throughout cloud partner and on-premises environments
• Diagnose failures across servers, DPUs, GPU systems, CPU systems, networking, Linux, and Kubernetes; turn recurring issues into automated detection and repair
• Define validation and handoff criteria so new capacity enters production safely and consistently
• Take part in on-call duties, incident response, root-cause analysis, and follow-up to implement permanent solutions
• Work with hardware, networking, platform, data center operations, and partner teams to resolve issues across ownership boundaries

Senior Software Engineer, SRE, Production Engineering

Full-stack Engineer

• Bring up, validate, and debug large-scale AI clusters, infrastructure, and end-to-end workloads
• Bring up, tune, and benchmark AI pre-training, post-training, and inference workloads using PyTorch, NeMo / Megatron, TensorRT-LLM, and adjacent NVIDIA AI software stacks
• Perform root-cause analysis of failures in large distributed environments
• Contribute to resilience and failure-attribution tooling that detects, triages, and attributes node, fabric, and workload failures across the cluster
• Build and maintain repeatable benchmark suites, automation, acceptance criteria, and qualification workflows on new platforms
• Tune runtime settings, communication parameters, and deployment configurations with framework, systems, and platform teams
• Deliver actionable, data-driven recommendations based on profiling, benchmark results, and cluster characterization

Software Engineer, DGX Cloud AI Infrastructure

Architect

• Contribute to the design of the next generation of high-speed IOs, including NVLink and NVLink-C2C
• Responsible for IO power optimizations and continuing to push energy efficiency
• Ensure interoperability with connected devices and system components in complex interconnect topologies
• Deep dive into technically challenging HSIO bugs and help drive debug efforts across various teams
• Work closely and proactively with system architects, mixed signal and design, DGX, software/firmware, HW/SW QA, operations, and AE teams to drive design, development, debug, and release of next-generation products

GPU/SOC Low-Power Feature Architect

• Design, develop, and verify features for next-generation SoC architecture in collaboration with hardware and software engineers
• Participate in early modeling and simulation required to produce products
• Work with hardware, silicon, and pre-silicon teams to bring up new platforms, products, and prototype systems
• Enable core OS software on new platforms during SoC bring-up
• Craft, develop, unit test, document, and maintain features for Tegra SoCs
• Create architecture and design specifications to influence hardware architecture and system software

System Software Engineer

• Act as the lead engineer for developing agent frameworks natively on Windows
• Build the technical roadmap for always-on, self-evolving AI assistants on GeForce RTX PCs and laptops
• Lead efforts to optimize agent runtimes for Windows
• Ensure autonomous agents operate within policy-based privacy and security frameworks
• Handle filesystem access, secure inference routing, and network egress
• Partner with internal AI research teams, driver teams, and the open-source OpenClaw community
• Help ensure consumer hardware provides an excellent ecosystem for autonomous agents
• Mentor engineers and establish guidelines for AI agent deployment
• Write reliable, production-ready code

Senior Engineer, Local AI – Agents and Systems

Technical Program Manager

• Lead the strategy and execution of programs supporting the bringup, operations and modernization of infrastructure for NVIDIA's Hardware EDA ecosystem
• Partner internally within Hardware Infrastructure and externally with senior management and other business-unit partners to scale the EDA Infrastructure charter
• Develop and standardize planning, reporting and execution methodologies and metrics
• Shape technical strategy, build programs and coordinate execution to scale bringups seamlessly, quickly and efficiently
• Drive continuous improvement across tooling, automation and cluster operations and management
• Guide engineering efforts through planning, prioritization, design, dependency management, implementation and execution using agile program methodology
• Apply metrics, OKRs and KPIs to measure program success and identify improvements
• Create communication channels for program status, risks and opportunities
• Serve as a technical and non-technical liaison among developers, customers and partners to drive alignment across a multifunctional matrixed organization

Senior Technical Program Manager – EDA Chip Infrastructure

• Lead strategy and execution of programs supporting bringup, decomposition, operations, and modernization of infrastructure for NVIDIA’s Hardware EDA ecosystem
• Partner with Hardware Infrastructure, senior management, and other business-unit partners to scale the EDA Infrastructure charter
• Develop and standardize planning, reporting, execution methodologies, and metrics
• Shape technical strategy, build and decommission programs, and coordinate execution to support seamless, fast, and efficient scaling
• Drive continuous improvement across tooling, automation, and processes for cluster build operations and management
• Guide engineering efforts through planning, prioritization, design, dependency management, implementation, and execution using agile methodology
• Apply metrics, OKRs, and KPIs to measure program success and identify improvements
• Create communication channels for program status, risks, and opportunities
• Liaise between developers, customers, and partners to align a multifunctional matrix of leads

Senior Technical Program Manager – EDA Cluster Builds and Decoms

• Work on profiling tools within the Nsight family
• Design and implement features for collecting, analyzing, and visualizing performance profiling data in cluster and cloud environments
• Contribute across the full product feature lifecycle, from prototypes to user demos
• Communicate across multiple teams to understand requirements, user needs, and expectations
• Apply knowledge of underlying hardware and software to deliver valuable user features
• Collaborate with team members across multiple time zones
• Interact with internal and external users, help them maximize product value, and deliver feedback to the product team

Senior Software Engineer, Developer Tools for Cloud

Solutions Engineer

• Serve as a trusted advisor mapping complex customer workloads to NVIDIA’s technology stack.
• Co-design scalable architectures with VMware, defining technical direction, integration milestones, and deployment plans.
• Design, validate, and support solutions for customer and partner success.
• Identify gaps between VMware needs and NVIDIA offerings and communicate insights to product and engineering teams.
• Lead technical engagements, troubleshoot complex issues, and advocate for customers’ technical needs.
• Drive technical enablement and adoption of NVIDIA SDKs, frameworks, and systems.
• Partner cross-functionally to ensure successful deployment and continuous improvement of NVIDIA solutions.
• Work with the VMware/Broadcom alliance team on joint validation, reference architectures, and roadmap feedback.
• Enable vGPU Compute for AI inference, LLM routing, accelerated data science, and agentic AI workloads.
• Support virtualization and workload management on NVIDIA hardware with Red Hat, SUSE, Nutanix, and other ecosystem partners.

Solutions Architect, Virtualization

Security Engineer

• Own the security vulnerability backlog for kernel and firmware components, driving timely triage, remediation, and SLA compliance
• Identify creative, scalable approaches to reduce vulnerability backlog growth
• Lead a continuous security pipeline involving scanning, triage, root-cause analysis, remediation, and validation across software and firmware components
• Communicate security risks, security posture, and remediation progress through metrics, reports, and stakeholder engagement
• Partner with engineering and security teams to define and execute long-term security strategy and product hardening efforts
• Drive and implement security reviews of software and hardware designs
• Assist others in ensuring product quality and robustness
• Evaluate, recommend, and develop security technologies, tools, and practices, including static analysis and dynamic fuzzing solutions

Security Engineer, GPU Kernel Driver

AI Engineer

• Build agentic workflows, including loops, graphs, and multi-step pipelines, for hardware network simulation and analysis
• Engineer workflow context from simulation models, specifications, design documents, and source code
• Collaborate with network architects to understand workflows and translate them into agent workflows
• Optimize simulation tooling runtime performance, including execution time, compute cost, and end-to-end latency
• Define evaluation and regression testing for agent workflows
• Build observability across agent runs, including actions, failures, and causes
• Champion secure and reliable agent workflow guidelines covering data handling, access control, and interaction boundaries
• Solve sophisticated integration issues between agents and internal tooling

Senior AI Engineer – Network Architecture

• Build, implement, and maintain installation, packaging, and software delivery workflows for NVIDIA networking software across major Linux distributions, including Debian, Ubuntu, RHEL, SLES, and NixOS
• Develop and provide ongoing support for meta-packages, software repositories, release channels, profiles, and tools for DEB/RPM and Nix package managers
• Build and implement automation solutions to improve package validation, release quality, and engineering efficiency, including AI-assisted development workflows
• Work with distribution maintainers and ecosystem communities, including Nix/NixOS, to ensure compatibility and smooth delivery through native packaging systems
• Perform system-level testing and verification of package installations on various platforms and OS versions
• Collaborate with kernel, QA, release engineering, architecture, and support teams to ensure installation quality, maintainability, and scalable software delivery
• Contribute to Linux kernel driver development and backporting to support advanced networking features