NVIDIA

Developer Relations

• Stay abreast of the latest developments in robotics, physical AI, digital twins, and develop proof-of-concept solutions for real-world applications
• Build and refine training materials and mentor team members solving real-world problems using NVIDIA Omniverse, Isaac Sim, Isaac Lab, Cosmos, and related stacks to create simulations, digital twins, and robotics workflows, etc
• Collaborate and provide feedback to NVIDIA product teams to help with product adoption, bugs, feature requests, and additional activities through our hackathon program
• Promote through publishing blogs and papers, facilitating presentations, and using other media that convey the impact of the work accomplished by teams at the hackathons
• Mentor developers and researchers to integrate NVIDIA technology using Omniverse, Cosmos, synthetic data, and coding-agent-assisted digital twins workflows to define architectures, compute footprints, test plans, and rollout strategies
• Strategize, identify, and assess potential sites, mentors, and key applications for Open Hackathons and Bootcamps
• Assess each hackathon's computing and software infrastructure
• Write comprehensive internal feedback reports and find opportunities for improvement

Senior Developer Advocate Engineer

Engineer

• Crafting, developing, and implementing advanced hardware solutions that power next-generation AI and computing platforms
• Collaborating with cross-functional teams to ensure seamless integration of hardware components
• Conducting rigorous testing and validation to deliver flawless performance in our products
• Analyzing and optimizing system performance to meet strict quality standards
• Partnering with software engineers to determine hardware requirements and ensure successful implementation
• Leading and mentoring junior engineers, encouraging a culture of innovation and collaboration.

Senior VLSI Engineer

Full-stack Engineer

• You and your teammates will own every part of the engineering mission of cuEST - from idea to shipped CUDA-X library.
• You will architect, implement, optimize, productize, and deploy production-grade GPU solutions for quantum chemistry library primitives in a collaborative environment.
• This includes technical leadership of specific code modules and general team-based contribution to engineering projects.
• Collaborating across broader engineering, product, and program organizations, you will take the developed products to market with a strong focus on partner and customer engagement.
• Engaging with the broader quantum chemistry community, contributing knowledge that helps drive adoption of GPU-accelerated quantum chemistry and carrying new developments from the field back to your teammates to accelerate our work.

Senior Software Engineer – Accelerated Quantum Chemistry, cuEST

QA Automation Engineer

• Allocate dedicated capacity to agent builds — contributing directly to the development of AI agents that support our security programs, including certifications, risk, and compliance.
• Build and maintain infrastructure to support agent workflows, including retrieval, context delivery, and agent-to-agent coordination patterns.
• Partner with team members to translate business needs into data-driven, agent-ready solutions that reduce manual effort and improve decision velocity.
• Architect and implement MCP pattern integrations that enable security agents to interact with data systems, tools, and APIs in a structured, scalable way.
• Own the design, deployment, and maintenance of ETL and agentic data pipelines to ingest, transform, and serve data from multiple sources into our data lakehouse and downstream agent consumers.
• Ensure data security, privacy, and governance are implemented across all pipelines and agent-accessible data surfaces.
• Continuously monitor, optimize, and resolve issues with data infrastructure, pipelines, and agents for efficiency, accuracy, speed, and scalability in support of real-time agent workloads.
• Mentor other engineers on data engineering, MCP patterns, and agent-native design principles.

AI Automation Engineer, Security

Software Engineer

• Characterizing AI workloads and deep learning models aimed at large-scale LLM training and inference on NVIDIA supercomputers.
• The role centers on distributed systems with a focus on high-performance networking and NVIDIA communication libraries.
• Benchmarking, profiling, and analyzing the performance to find bottlenecks and identify areas for improvement and optimizations, with a strong emphasis on networking aspects.
• Developing PyTorch trace-based profiling, analysis, and replaying toolset to aid in benchmarking, debugging, and co-designing network systems for LLM workloads.
• Collaborating with multiple teams from hardware to software to provide performance analysis insights.
• Defining performance test plans, setting performance expectations for new technologies and solutions, and working to achieve performance targets.

Principal Developer, AI Networking

Systems Engineer

• Design, deploy, and maintain scalable software services that ensure transactional integrity and manage high-volume ingestion of billions of metering events.
• Develop complex rating engines for multi-dimensional pricing while integrating external tax engines to ensure global accuracy and regulatory compliance.
• Build and maintain pipelines for generating immutable, localized PDF invoices that meet strict regulatory requirements.
• Partner with cross-disciplinary teams to translate business needs into software solutions, managing project priorities to ensure timely delivery.

Senior Software Engineer – Financial Systems Engineering

Solutions Engineer

• Serve as a Solutions Architect part of GPU Private Cloud team used by thousands of NVIDIANs globally for interactive development, centralized CI / CD and QA testing, with an opportunity to positively impact all of the SW development teams across NVIDIA.
• Evaluating, identifying and developing software solutions to optimize critical software development workflows across various organizations within Nvidia.
• Architecting, Implementing & supporting end-to-end CI/CD system using open-source and Nvidia proprietary software.
• Customer (NVIDIA Internal development teams) onboarding to Private cloud infrastructure with a good discovery of the use case and available solutions within the cloud
• Identify performance bottlenecks and optimize the speed and cost efficiency of AI development and testing systems.
• Leading software development projects and technically direct a team of brilliant engineers and guide them to provide efficient and impactful solutions.
• Looking for problems within software systems and resolving the issues
• Craft and implement critical metrics using various analytics methods and dashboards

Senior Solutions Architect, IPP

• Guide the design and implementation of a new LLVM-based backend JIT compiler targeting NVIDIA GPUs
• Design and develop new compiler passes and optimizations required to meet the high-performance and low compilation time requirements of the compiler
• Work with global compiler, hardware and application teams to oversee improvements and problem resolutions
• Apply and adapt the latest compiler technologies to produce premier, robust, supportable compilers and tools
• Get a chance to influence and work on new GPU architectures

Raytracing Compiler Engineer – Developer and Performance Technology

• Verify the build and implementation of the industry's leading GPUs
• Verify the micro-architecture using formal verification tools
• Define the verification scope and ensure correctness
• Employ sophisticated formal techniques to acquire sufficiently bounded proofs
• Work with architects, designers, and pre- & post-silicon verification teams
• Complete the formal verification effort for the entire project cycle

Senior Formal Verification Engineer

DevOps Engineer

• Design, implement, and maintain large-scale HPC/AI clusters
• Utilize and develop tools to manage infrastructure as code
• Develop and maintain CI/CD pipelines
• Develop automation scripts and tools to automate deployment
• Perform comprehensive troubleshooting from bare metal to application level
• Serve as a technical resource, developing and sharing best practices with internal teams
• Support R&D activities and engage in POCs and POVs for future improvements

Senior HPC DevOps Engineer

• Design and build software code and cloud services for Data Management, including providing a catalog, managing metadata and life cycle of datasets and checkpoints
• Connect with other technical leaders across NVIDIA to ensure you are using existing technologies where possible and that we are collaborating appropriately with their systems
• Collaborate with the NVIDIA research team to utilize new storage and compute innovations, including GPU direct storage and DPU

Senior Software Engineer, DGXC Data Services

• Partner with NVIDIA Engineering, Product, and Sales teams to secure design wins at customers.
• Enable development and growth of NVIDIA product features through customer feedback and proof-of-concept evaluations.
• Perform proof-of-concepts working side by side with clients, engineers, and other architects on in-depth analysis, profiling and optimization of machine learning/deep learning models to ensure the best performance on current- and next-generation GPU architectures.
• Work directly with client ML researchers and developers/engineers on business-impacting workflows, projects, and issues to drive success using NVIDIA technology.
• Facilitate rapid resolution of customer issues and promote the highest levels of customer satisfaction.
• Build collateral (notebooks/ blogs) applied to Finance industry use-cases such as ML/DL, recommender systems, GNN, monte-carlo simulations, Quantitative Finance, etc. by working closely with customers.

Senior Solutions Architect, Financial Services – Capital Markets

• Build AI-native, self-healing CI workflows for large Tegra C/C++ codebases
• Design fast build, test, and validation paths that keep developers and agents in tight loops
• Integrate reasoning agents that can triage failures, recommend fixes, and safely automate routine recovery
• Improve incremental builds, caching, remote execution, and test selection
• Integrate simulation, emulation, and device-backed testing into trustworthy CI
• Build machine-readable outputs, policies, and recovery paths that agents can safely use at scale
• Package workflows and platform capabilities so other teams can reuse them
• Drive adoption with metrics, docs, and hands-on enablement

Senior Software Engineer, AI Speed Infrastructure

Security Engineer

• Design and deploy AI agent systems for security workflows: PQC transition, attacker-defender frameworks, threat modeling, and automated mitigation deployment.
• Build frameworks integrating LLMs, RAG, and automation pipelines with security data sources and engineering workflows.
• Partner with product and architecture organizations to embed security requirements early and translate threat landscapes into scalable solutions.
• Own the full agentic system lifecycle: architecture, prototyping, productization, testing, and operational stewardship.

Senior System Security Architect

Program Manager

• Own and lead the AI Factory ARB process end to end, from initial intake through operations and pre-deployment handoff.
• Lead architecture governance, assessments of deployment preparedness, and the validation and sign-off activities for complex AI Factory deployments.
• Coordinate account teams, solution architects, NVIDIA infrastructure specialists, engineering, networking, storage, security, facilities, operations, OEM partners, and NVIDIA Cloud Partner teams.
• Manage ARB schedules, agendas, decision logs, action owners, risk tracking, blocking issues, and executive reporting.
• Set and maintain deployment gates, design checkpoints, exception handling, and sign-off processes aligned to NVIDIA Reference Architectures, Reference Designs, and deployment standards.
• Review ARB submissions, classify requests by review path, prepare teams for timely decisions, and maintain clear documentation in shared workspaces.
• Coordinate remediation and exception paths for designs that do not meet Reference Architecture or Reference Design criteria, including approval tracking and follow-through on blocking issues.
• Improve ARB templates, tools, documentation, reporting, automation, and AI-assisted workflow agents; partner with global teams to scale ARB governance across regions and partners.