NVIDIA

QA Automation Engineer

• Oversee and optimize compute and storage resources, ensuring operational efficiency and success of VLSI projects.
• Develop and maintain scripts, automation tools, and AI-assisted workflows to streamline infrastructure tasks and improve developer productivity.
• Design, implement, and maintain dashboards for monitoring and reporting on infrastructure performance and usage.
• Work closely with a remote team in Israel, ensuring smooth communication and coordination on infrastructure-related tasks.
• Engage in the entire lifecycle of infrastructure tool development, including design, testing, deployment, and maintenance.
• Collaborate with other team members and DA teams to implement innovative software solutions and agentic coding practices using modern AI tools.

VLSI Design Automation Software Engineer

AI Engineer

• Contribute features, fixes, and optimizations upstream to vLLM/SGLang
• Implement and optimize inference‑runtime capabilities
• Profile and improve hot paths across layers
• Improve multi‑GPU inference performance and reliability
• Build and maintain performance and correctness regression tests
• Collaborate with model, platform, and SRE teams

Senior Software Engineer – AI Inference

Hardware Engineer

• Verify the design and implementation of the industry's leading GPUs
• Responsible for verification of the ASIC design, architecture, golden models and micro-architecture using advanced verification methodologies such as UVM
• Understand the design and implementation of your unit, define the verification scope, develop the verification infrastructure and verify the correctness of the design
• Collaborate with architects, designers, and pre and post silicon verification teams to accomplish your tasks

ASIC Verification Engineer – GPU

• Design and build performance analysis tools and workflows for AI training and inference workloads.
• Understand how AI performance engineers work and translate their needs into scalable, intuitive tooling.
• Develop integrations between profiling infrastructure and AI frameworks and workflows.
• Collaborate with performance engineers, hardware architects, and software teams to ensure profiling capabilities align with real-world AI workloads.
• Identify performance bottlenecks in AI workloads and develop automated approaches to detect and diagnose them.

Senior Software Engineer, AI Performance Analysis

• Use AI for solving product problems in gaming and other interactive experiences.
• Build upon the latest research to create new models and invent new ways of applying AI to advance neural graphics and gaming.
• Create prototypes to demonstrate real-life applications of your ideas and to accelerate productization.
• Keep up with the latest AI/DL research and collaborate with diverse teams (both internal and external to NVIDIA), including AI/DL researchers, hardware architects, and software engineers.
• Participate in technology transfers to and from teams across NVIDIA.

Senior Machine Learning Graphics Engineer, AI for Experiences

Engineering Manager

• Lead and grow a multi-team engineering organization, setting a high bar for software quality, service reliability, and engineering culture.
• Own roadmap execution for NVIDIA's internal object storage service — partnering with internal customers, Product Management, and Architecture to translate multi-quarter goals into clear engineering plans with measurable milestones.
• Drive development and operation of NVIDIA's S3-compatible object storage service, ensuring it meets the performance, durability, availability, and scalability demands of AI training and inference workloads at exabyte scale.
• Lead the Data Movement Tools team in building and evolving tooling that stages datasets, model checkpoints, and artifacts from distributed storage to GPU-adjacent compute — minimizing I/O bottlenecks and keeping accelerators fully utilized.
• Define and uphold service reliability standards: SLOs, capacity planning, incident response, root cause analysis, and on-call hygiene.
• Partner with SRE to ensure the platform meets the availability commitments internal customers depend on.
• Establish and enforce engineering standards across both teams: design reviews, code quality, CI/CD practices, automated testing, and production observability.
• Recruit, mentor, and develop engineers across all levels, conducting regular 1:1s, performance cycles, and career growth conversations.
• Build a diverse, inclusive, and high-retention team.
• Collaborate closely with SRE, Platform, Networking, and Security teams to ensure smooth transitions from development to production and rapid resolution of customer-impacting issues.
• Champion the adoption of AI-assisted development tooling — coding assistants, agentic workflows, and automated testing harnesses — to accelerate team productivity and raise engineering output.
• Represent the Object Storage engineering organization to senior leadership, providing transparent status updates, surfacing risks early, and advocating for the resources needed to succeed.

Senior Engineering Manager, Object Storage – DGX Cloud

Systems Engineer

• Design, build, and deploy highly scalable cloud-based solutions
• Architect and manage Kubernetes clusters with custom components
• Build advanced CI/CD pipelines and workflows
• Design observability solutions and tooling
• Mentor team members and drive best practices

Senior System Software Engineer – Cloud, GeForce NOW

Solutions Engineer

• Collaborating closely with customers to improve their workload performance and reduce infrastructure costs.
• Leading and developing proof-of-concepts for AI solutions applied to the Consumer Internet industry, including areas like LLMs and recommenders, and building collateral (notebook/code) as needed.
• Developing and debugging software for NVIDIA and open-source AI frameworks and libraries.
• Partnering with NVIDIA’s software engineering, product, and sales teams to secure design wins and drive the development of innovative solutions based on customer feedback.

Solutions Architect, Agentic Optimization

Full-stack Engineer

• Track the cutting edge: How are agentic systems evolving? You'll follow research in tool use, planning, memory, evaluation, self-improvement, multi-agent workflows, runtime infrastructure, and agent safety/security.
• Bridge research and product: Identify research ideas that can meaningfully improve OpenShell and translate them into concrete product opportunities.
• Benchmark and adapt: Reproduce and test promising methods from papers, open-source projects, industry work, and internal NVIDIA research.
• Build rapid prototypes: Create hands-on proof-of-concepts using OpenShell, including agent harnesses, evaluation loops, self-improving workflows, and runtime-native developer experiences.
• Red-team systems: Design evaluation and red-team harnesses that measure agent reliability, usefulness, scalability, safety, security, and developer experience.
• Secure the workflow: Help us design secure-by-default workflows for agents operating with tools, code, files, credentials, and enterprise systems.
• Partner across teams: Collaborate closely with engineering, product, design, research, solutions, and developer-facing teams to move ideas from prototype to product.

Software Engineer, OpenShell

• Designing and implementing new features for high-performance CPUs and GPUs
• Working with application teams to tackle interesting and meaningful compilation problems
• Partnering with team members on projects as related to high-performance computing and optimizations
• Interacting directly with teams in the open source community

Senior CPU Compiler Engineer – HPC

Production Engineer

• Build and operate automation for large-scale GPU clusters across NVIDIA Cloud Partners (NCP) and on-prem environments
• Develop tools and services for provisioning, validation, upgrades, monitoring, repair, and cluster lifecycle operations
• Improve Day 0 / Day 1 / Day 2 workflows for cluster bringup, handoff, and production operations
• Reduce manual production touches through APIs, GitOps, automation, and agent-assisted workflows
• Participate in on-call, incident response, debugging, and durable follow-up work
• Partner with platform, storage, networking, security, and workload teams to make infrastructure production-ready

Senior Software Engineer, DGX Cloud Production Engineering

• Working with NVIDIA AI Native and Consumer Internet customers on large data center GPU server and networking system deployments as Solution Architect Engineer.
• Guide customer discussions on network design, compute/storage and support bring up of server/network/cluster deployments.
• Demonstrate subject matter expertise in advanced GPU & network systems and be a trusted technical advisor to NVIDIA's strategic customers.
• Bring customer-specific requirements to product teams to guide product roadmap features.
• Identify new project opportunities for NVIDIA products and technology solutions in data center and artificial intelligence applications.
• Work closely with the GPU/Network Systems Engineering, Product management and Sales teams
• Work as customer trusted advisor conducting regular technical customer meetings for product roadmap, cluster issues debug, feature discussions and introduction to new technology solutions
• Build custom product demonstrations and POCs for solutions that address critical business needs of our customers
• Analyze and debug compute/network configuration, performance issues to deliver performant clusters

Senior Solutions Architect, AI Infrastructure

• Design, build and optimize agentic AI systems for the CUDA ecosystem.
• Co-design agentic system solutions with software, hardware and algorithm teams; influence and adopt new capabilities as they become available.
• Develop reproducible, high-fidelity evaluation frameworks covering performance, quality and developer productivity.
• Collaborate across the AI stack—from hardware through compilers/toolchains, kernels/libraries, frameworks, distributed training, and inference/serving—and with model/agent teams.

High Performance AI Engineer

Product Manager

• Take full responsibility for the strategic direction and roadmap of the break-fix automation system.
• Define automation confidence thresholds, blocking issue criteria, and human-in-the-loop intervention points.
• Build the operator UX for repair queues, workflow transparency, and audit trails.
• Drive the integration between failure attribution and automated repair actions.
• Define repair SLOs and own the metrics framework for time-to-drain, time-to-healthy, and overall fleet availability.
• Collaborate with NCP operators, SRE teams, and hardware vendor partners to integrate RMA processes and optimize repair workflows at scale.

Principal Product Manager

DevOps Engineer

• Develop and support CI processes of various products.
• Coordinate with various teams across the globe to promote and improve CI practices.
• Build infrastructure for effective, high-quality development and release efforts.
• Be a part of an experienced team with a great atmosphere.