NVIDIA

Engineer

• Work closely with diverse teams of engineers to derive functional and safety requirements
• Contribute to architecture decomposition and architecture validation
• Guide teams in system safety engineering methodologies
• Collaborate on V-Model process improvements

Senior Systems Safety Engineer – Autonomous Vehicles

Full-stack Engineer

• Direct the building and refinement of CAPI providers for NVIDIA Kubernetes Engine, maintaining steady, consistent, and scalable node provisioning across DGX Cloud and NCP environments
• Develop and maintain bring-your-own-node workflows that allow customers to integrate different NVIDIA hardware into NKE clusters while ensuring high operational consistency
• Coordinate OS image generation, packaging, deployment, and update processes for NKE nodes
• Ensure images are fine-tuned for NVIDIA GPU workloads and satisfy enterprise- and cloud-grade security and compliance criteria
• Develop and sustain node image hardening pipelines, incorporating CIS benchmarks, automated CVE remediation, and promotion gates connected to security posture
• Develop and maintain automated test suites for node images
• Handle nodepool lifecycle at scale, including provisioning, upgrades, drain and cordon workflows, and seamless node replacement across very large clusters with diverse NVIDIA hardware
• Examine, resolve, and determine underlying causes of node-layer faults in production NKE clusters
• Communicate your progress and findings at internal and external gatherings such as KubeCon and GTC

Senior Systems Software Engineer – Kubernetes Node Lifecycle

• Develop software systems to support large scale deployments of cloud infrastructure
• Design and develop APIs to support Infrastructure as Code (IaC) automation and deployment workflows.
• Responsible for contributing to multiple source code projects to fulfill NVIDIA requirements with software services
• Work and collaborate with engineering managers, architects, designers, and frontend engineers to deliver high quality software
• Automate the validation of software solutions with unit and integration tests
• Participate in the ownership and health of CI/CD pipelines from dev to production environments
• Collaborate with other specialists for feedback on proposed designs and product direction
• Openly share successes and failures in a no blame environment

Cloud Platform Software Engineer – Platform APIs

Solutions Engineer

• Partner with our business/account team working with customers to develop a keen understanding of their goals, strategies, and technical needs and to help define and deliver high-value solutions.
• Stay up to date on the state of the art in image/video analysis and sensor processing to apply the latest advancements in the field to customer needs.
• Technical Problem Solving: Diagnose and resolve system issues and performance bottlenecks across the full AI stack, from initial model selection to large-scale deployment.
• Multi-functional Collaboration: Work alongside NVIDIA’s internal engineering, research, and product teams to resolve critical partner challenges and speed up shared achievements.
• Document what you know and teach others. This can vary from building targeted training for partners and other Solutions Architects, to writing whitepapers, blogs, and wiki articles, to simply working through hard problems with a customer on a whiteboard.
• Partner strategically with industry-specific solution partners targeting our computing platform.
• Some travel is required for this role.

Solutions Architect – MedTech

• Drive end-to-end performance and scale characterization for the NVIDIA DGX Cloud software stack
• Collaborate with AI researchers, developers and customers to develop innovative, automated tests
• Deep dive into performance and scale issues in complex distributed systems
• Design and develop monitoring, reporting and analysis tools for performance and scale testing
• Triage, debug and root cause issues related to operating Kubernetes clusters at ultra-large scale
• Build and maintain a high-velocity framework that enables continuous, always-on performance and scale testing
• Document research, methodologies and results clearly
• Engage efficiently with upstream communities

Senior Systems Software Engineer, Kubernetes Scale - DGX Cloud

• Decomposing and modularizing build processes for reusablity across multiple projects
• Debugging CMake, pip, and conda issues encountered in CI and local builds
• Working on scripting and infrastructure to manage dependencies across various environments and build systems
• Bringing up builds and CI across platforms (x86_64/arm64) and OSes (Linux/Windows/Mac) and other unreleased hardware and software
• Working with engineering leadership to identify the support matrix and manage the scope of the build matrix
• Automating scheduled work for all of the above

Senior Build Engineer – CUDA Driver, Libraries

• Apply your knowledge of debuggers, binary instrumentation and computer architecture to enhance existing compute debugger tools and libraries, and extend them to new use cases.
• Architect, design, and implement solutions to integrate new debugger features into existing NVIDIA developer tools products.
• Collaborate closely with research, libraries, and product teams at NVIDIA to identify debugger features that can effectively improve developer productivity and efficiency.
• Document requirements and designs, and review documents with teams throughout NVIDIA.
• Develop the compute debugger tools for GPUs running on Linux, Windows, and embedded operating systems.
• Effectively estimate and prioritize tasks in order to create realistic delivery schedules.
• Provide peer reviews to other engineers, including feedback on performance, scalability and correctness.
• Mentor junior engineers.

Senior Debugger Software Engineer

Security Analyst

• Lead Incident Response efforts for corporate, cloud, and product environments, including investigation, containment, eradication, and recovery.
• Perform threat hunting across endpoints, networks, and cloud workloads to proactively identify indicators of compromise, emerging threats, and control gaps.
• Conduct cloud incident response for AWS, Azure, and GCP, and other cloud environments including Kubernetes and containerized workloads, performing log analysis, identity compromise investigations, and workload forensics.
• Drive product security incident response, collaborating with engineering teams to analyze potential exposure to vulnerabilities, exploits, and security flaws in NVIDIA products.
• Perform digital forensics and malware analysis to support investigations and root cause analysis.
• Develop and optimize security orchestration and automation playbooks in partnership with Security Engineering to accelerate detection and response.
• Build and refine detections and defense strategies based on threat models and attacker behaviors across cloud, identity, endpoint, and product telemetry, using frameworks such as MITRE ATT&CK to map adversary tactics and enhance detection coverage.
• Provide guidance to engineering and business teams on secure design and incident handling standards and contribute to security policies, standards, and metrics to continuously improve NVIDIA’s security posture.

Cyber Security Analyst

• Train, fine-tune, optimize and customize perception DNNs in low precision (FP16/INT8)
• Apply sophisticated quantization of DNNs
• Improve DNN architectures using ML algorithms on NVIDIA GPUs or DLAs
• Continuously improve inference speed, accuracy and power consumption of DNNs
• Stay up to date with the latest research and innovations in deep learning, implement and experiment with new insights to improve NVIDIA's automotive DNNs.

Senior Deep Learning Software Engineer – Autonomous Vehicles

• Verify the design, architecture and micro-architecture using advanced verification methodologies
• Define the verification scope, and contribute to development of verification infrastructure for memory subsystem units
• Verify firmware code, with specific attention on verifying hardware/firmware interactions
• Collaborate with architects, designers, software engineers across sites to accomplish your goals

ASIC Verification Engineer, New College Grad 2026

Product Manager

• Contribute across the full lifecycle of the NVIDIA AIOps platform —from shaping business strategy and influencing software development tradeoffs to supporting direct and partner-led go-to-market execution
• Work closely with customers including demos and driving field trials to ensure successful adoption.
• Translate customer needs into shipped capabilities.
• Define specific features with user experience details and technical requirements
• Define use cases to craft and convey the product value proposition to a variety of audiences.
• Help define future products and build prototypes to convey value proposition and competitive differentiators
• Build UI mocks to effectively communicate user experience, customer value and design requirements.

Senior Product Manager – AIOps

DevOps Engineer

• Working on building tools to improve the SRE Observability.
• Be part of the Kubernetes migration journey with VMI setup and problem solving.
• Rapidly debug and triage incidents and user-reported issues
• Taking ownership of automating, scripting, and tooling of new/existing scripts to help the team achieve 100% automation of daily tasks
• Support services before they go live through activities such as system design consulting, developing software platforms and frameworks, capacity management and launch reviews.
• Be part of an on-call rotation to support production systems

Senior Site Reliability Engineer, GeForce NOW

• Build and implement production-grade features across NemoClaw, focusing on onboarding flows, policy controls, inference routing, and sandbox lifecycle.
• Develop and sustain secure agent runtime infrastructure, ensuring strong network policy administration, credential management, and failure recovery.
• Engage in daily open-source workflows: author pull requests, conduct technical reviews, address issues, write tests, and contribute to documentation.
• Use AI-assisted development tools to improve the engineering loop, while applying rigorous verification and security measures.
• Develop tools, test harnesses, automation scripts, and CI/CD workflows to boost team efficiency.
• Diagnose complex failures across various platforms and environments, including TypeScript/Node.js, containers, Linux, macOS, WSL, and GPU-backed systems.
• Collaborate with internal teams and external communities, including OpenShell and AI platform partners.

Senior Software Engineer, AI Agent Runtime, Open Source Infrastructure

Systems Engineer

• Design, deploy, and operate solutions on Kubernetes for large-scale storage and data platforms, including the manifests, Helm charts, and operators that run them.
• Build tools, services, and automation that improve the lifecycle of storage and data systems – from provisioning and configuration through deployment, scaling, and day-2 operations.
• Develop and operate telemetry and observability for production systems – metrics, logging, tracing, dashboards, and alerting – so that system health, availability, and latency are measurable and actionable.
• Apply strong analytical troubleshooting skills to diagnose and resolve complex issues across distributed, containerized infrastructure.
• Work closely with peers and partner teams to improve the lifecycle of services, from inception and design through deployment, operation, and refinement.
• Scale systems sustainably through automation, infrastructure-as-code, and CI/CD, and evolve systems by pushing for changes that improve reliability and velocity.
• Support services before they go live through activities such as deployment automation, capacity planning, and launch and readiness reviews.
• Practice sustainable incident response and postmortems, and participate in an on-call rotation to support production systems.

Senior Systems Engineer, Storage – DGX Cloud

• Design, build, and operate the infrastructure backbone powering AI inference products
• Own Kubernetes deployments end-to-end
• Architect CI/CD pipelines for automated build, test, packaging, and release
• Build observability that tells the truth about platform health
• Manage cloud and on-prem environments with infrastructure-as-code
• Own the security posture for infrastructure components
• Collaborate closely with engineers across teams