NVIDIA

Mechanical Engineer

• Develop and participate in cutting edge Processor design in deep submicron technologies
• Work as part of a global circuits team to design innovative circuits (digital, semi-custom and mixed-signal analog) for silicon correlation and hardware security
• Collaborate and work closely with cross-functional teams to improve the performance, reliability and security of Nvidia’s next generation products by performing detailed transistor-level analysis on the design
• Drive the design and physical implementation of digital and/or mixed-signal analog circuit IPs for current and voltage sensing, and common Security attacks detection and protection using custom and automated tools
• Create prototypes of patentable ideas on test chips and drive them to be deployed across the entire line of products
• Be a mentor/technical lead for junior team members

Circuit Design Engineer

DevOps Engineer

• Designing and supporting mechanisms for coordinating and maintaining a large number of semiconductor design tasks across multiple datacenters.
• Building web interfaces to configure, launch and analyze tools.
• Debugging and improving services on platforms ranging from web browsers to containerized services to bare metal Linux hosts.
• Data mining and analyzing large datasets of job execution telemetry and tool Quality of Result to improve flows.
• Helping to invent the next generation in semiconductor design methodology.
• Optionally, contributing to the physical design of GPU/CPU/Networking products.

Physical Design Methodology, DevOps Engineer

Full-stack Engineer

• Build and redesign tooling, services, and workflows that encompass all products on GFN
• Adapt and scale services for both internal and consumer-facing applications
• Investigate and develop future ideas for our pixel streaming + AI product, GDN
• Own and standardize AI workflows to streamline development and UI build
• Collaborate with engineers, designers, and TPMs to bring products to life successfully

Senior Software Engineer, Cloud Streaming

Infrastructure Engineer

• Lead how NVIDIA responds to and adapts to growth and rapid change.
• Drive the organization’s program design and execution.
• Collect requirements, define priorities, coordinate scheduling, and address challenges throughout the implementation lifecycle.
• Optimize workflow using objective measures to improve engineering efficiency.
• Establish a Program Management charter based on accountability, outcomes, leadership, and delivery.
• Set and clearly define high standards and help the team achieve them.
• Hire, retain, and grow outstanding people.
• Drive high performance, clarity, positive culture, and collaboration.

Director, Infrastructure Engineering – Program Management

Machine Learning Engineer

• Convert research into real products (not just slide decks or notebooks)
• Help build workflows that diversify datasets and/or populate data
• Ship machine learning workflows/pipelines fast and iterate faster
• Leverage LLM/VLM and agents in the data generation pipeline
• Define evaluation criteria and run offline evals before any model or prompt change reaches production

Senior Systems Software Engineer, Machine Learning

Technical Program Manager

• Lead cross-functional programs across product, engineering, platform, ecosystem, and go-to-market teams.
• Drive planning and execution for cloud and software platform roadmaps, including integration paths, release readiness, and delivery dependencies.
• Build coordinated plans for early product proof points, customer-facing workflows, and high-visibility technical demonstrations.
• Align internal teams and external partners on readiness criteria, dependency closure, enablement material, and pilot-to-scale handoffs.
• Clarify priorities, surface tradeoffs, drive decisions, and maintain operating rhythms across complex technical programs.
• Help mature early initiatives into repeatable offerings that customers and partners can adopt with confidence.

Senior Technical Program Manager, DSX Sim

• Design, implement, and own scalable, high-performance software libraries, features and services across the stack.
• Contribute to software architecture and technical design across multiple components and frameworks, with an emphasis on robustness, flexibility, and long-term maintainability.
• Help define projects and execution plans by clarifying scope, identifying dependencies and tradeoffs, and translating broad goals into actionable technical work.
• Provide technical leadership to a team or multi-functional group by guiding implementation, reviewing design and code, and helping drive progress against timeline and strategy.
• Operate effectively in ambiguous spaces, making sound technical decisions and moving work forward with a high degree of autonomy when needed.
• Build and iterate on AI-assisted development workflows, including code generation, refactoring, CI/CD automation, and practical use of coding agents in real engineering environments.
• Collaborate with robotics and simulation teams to integrate services and tools into robotics workflows and, where relevant, extend platforms such as Isaac or ROS.
• Contribute to strong engineering practices around testing, code review, documentation, observability, reliability, and operational quality.

Senior Systems Software Engineer – Omniverse

Security Engineer

• Constantly improve automation, develop new tools and skills that make our secure practices easier for users to adopt and deploy
• Partner with engineering and product management from earliest design through release. This entails tracking evolving discussions, surfacing security implications, and translating them into practical mentorship
• Run security reviews across code, dependencies, containers, cloud, and CI/CD
• Triage, prioritize, and drive remediation to closure
• Build automation and developer-facing tooling that make secure-by-default the easy path
• Ask sharp questions. Challenge assumptions. Surface risks that don't appear on standard checklists
• Improve secure development practices, standards, and workflows
• Communicate risk crisply to technical and non-technical audiences
• Stay ahead of emerging threats relevant to modern software and cloud.

Information Security Engineer

• Research, design, develop and implement architecture solutions (Hardware and software) meeting internal and external security requirements and standards.
• Apply innovative hardware security primitives to enable next generation secure software extensions supported by hardware.
• Design next generation production and provisioning systems.
• Collaborate with partners on the implementation of open-source software.
• Collaborate across the company to guide the direction of Its (USB, I2C, I3C, UART, PCI) working with hardware, software, research and product teams.
• Architectural modeling, validation, microarchitectural definition, following standards bodies, and developing infrastructure enabling trusted platforms using hardware security methods.
• Work with customers, partners to identify and address security issues and threats.

Senior Silicon Security Architect

Architect

• Develop our simulation model to enable research and analysis of new technologies.
• Use our simulation model to define the next generation of our products.
• Be part of the team that defines the ConnectX Network Adapter chip and Bluefield Data Processing Unit architecture end to end from the market requirements through design and all product life cycles (post/pre-silicon, on deployments).
• Collaborate with other research teams.

Senior Network Modeling Architect – Networking

• Thoroughly understand our networking solutions across all performance related aspects.
• Develop a C++ simulation model to define and evaluate architectural options for our next generation of networking products.
• Understand different trade-offs related to solving performance bottlenecks.
• Collaborate and lead technical solutions within architecture, research, hardware, and software teams.
• Analyze and model the communication patterns of key DL, GAI, inference, and training applications.
• Explore innovative ideas to improve and optimize our chip systems performance.

Performance Modeling Architect

Hardware Engineer

• Take part in research, design, and development of QoS and FW algorithms
• Provide hw-aware technical guidance for core FW development
• Work closely with the architecture and different software design teams
• Implement new features in the core of NVIDIA NIC Firmware
• Develop verification tests for advanced features in a sophisticated Firmware testing environment
• Gain a deep understanding of system debug, networking technology and stacks

Senior Firmware Engineer

Engineering Manager

• Lead and manage a team of software engineers developing network simulation and testing solutions
• Drive the design and development of scalable simulation environments and automated testing frameworks
• Collaborate with networking, software, QA, and infrastructure teams to validate next-generation networking technologies
• Support development and debugging activities across complex simulated environments
• Improve development workflows, CI/CD processes, automation, and software quality practices
• Mentor engineers and foster a strong technical and collaborative team culture
• Contribute to technical decision-making, prioritization, and execution planning

Manager, Software Engineering – Network Simulation and Testing

Artificial Intelligence

• Drive hands-on safety and security research on a range of AI and networking products
• Develop tools and processes to expose novel weaknesses in AI models and systems to preempt threats
• Participate in defining and ensuring AI development processes meet safety and security standards
• Partner with cross-functional teams to understand needs and implement solutions
• Be a technical focal point across multiple teams and provide hands-on AI safety, security and engineering expertise

Senior AI Safety Red Teamer

• Developing, implementing and improving models and algorithms across media types, whether time series, images, text, audio or video.
• Leveraging data pipelines to efficiently process and transform large volumes of data for training and inference purposes.
• Optimizing and fine-tuning models for performance, scalability, and resource utilization, considering factors such as latency, efficiency, and cost.
• Creating efficient pipelines for model training, feedback and improvement.
• Applying alignment techniques and parameter efficient fine-tuning to improve model performance.
• Measuring and benchmarking model and application performance to drive improvements.
• Driving the gathering, building, and annotation of domain specific datasets for benchmarking and training.
• Collaborating closely with software and hardware engineers on new features and improvements.
• Participate in developing and reviewing code, design documents, use case reviews, and test plan reviews.