NVIDIA

Backend Engineer

• Participating in an international team of software engineers working on products for testing NVIDIA ethernet networking products.
• Designing and implementing robust, maintainable, and efficient automation test suites for end-to-end testing of AI ethernet networks.
• Engaging directly with NVIDIA customers to ensure we are aligned on their networking requirements and solve their problems.
• Debugging and diagnosing complex networking problems.

Senior Software Engineer – Python, Spectrum-X

Systems Engineer

• Identify, diagnose, and addressing high-value problems during the product onboarding process
• Verify that all integrated components interact as intended
• This includes functional testing to ensure software components work correctly on various hardware testing platforms
• Validate firmware features for production at hardware power-on stage
• Bridge between software, production and customer engineering teams

Firmware System Engineer

Business Development Rep

• Identifying and developing new business opportunities for NVIDIA's EDGE Computing as well as growing the business of Jetson products.
• Building and maintaining positive relationships with key customers by successfully implement NVIDIA sales strategies.
• Parallelly manage the ongoing projects with accurately timeline and strategic thinking.
• Establish the comprehensive eco-system of Embedded AI and build the platform which could collaborate with all partners to provide the end to end solution to the customers.
• Collaborating with cross-functional teams to package NVIDIA full stack software & optimization to fulfill the market needs and develop tailored solutions.
• Analyzing market trends and competitor activities to ensure NVIDIA remains a world-class leader in the industry.

Business Development Manager, EDGE Computing

Account Manager

• Build, grow, and maintain strong relationships across the partner organization, from technical teams to senior leadership and C‑level executives, securing alignment and commitment on joint priorities and initiatives.
• Develop a deep understanding of the partner’s solutions, architecture, and internal infrastructure, identifying where NVIDIA platforms, software, and services can bring clear business and technical value.
• Act as the “feet on the ground” for critical and complex support cases, ensuring timely resolution and clear communication when hands-on engagement is required.
• Coordinate closely with relevant NVIDIA product, solution, and engineering groups to align roadmaps, resolve issues, and jointly shape solutions for the partner.

Software Engineer

• Engage directly with the developer community and experts in their field
• Guide key framework and application developers
• Contribute directly to their software stack or develop reference code
• Join efforts with diverse groups at NVIDIA to improve products
• Influence the design of NVIDIA next-generation architectures

Senior CPU Performance Developer

Developer Relations

• Understand China researcher and developer communities, Analyzing the technical requirement, identify needle moving projects
• Bridge NVIDIA tools with communities' requirements, Promote NVIDIA tools, libraries, and SDK’s with China researcher and developer communities, ISV and Service Providers
• Deeply understand CAE/EDA software ecosystem and related acceleration and AI approaches
• Discover new workflows, identify blockers to ISV adoption, and report back to the product teams
• Drive early adoption of new products and support launch and go-to-market activities
• Collaborate with NVIDIA business development managers, solution architects, developer technology engineers, developer marketing, product teams to engage with customers and communities
• Make heavy use of conferencing tools, but some travel is required

Senior Developer Relations Manager

Computer Vision Engineer

• Stay up to date with the latest research and innovations in deep learning, implement and experiment with new ideas.
• Foster collaborative partnerships with our researchers and engineers, transforming innovative research into robust, industrial-strength machine learning models.
• Taking approaches from initial evaluation and experimentation all the way to shipping.
• Defining and collecting training datasets.
• Building training pipelines and real-time inference run-times (PyTorch, TensorFlow, TensorRT, Python, C++).

Senior Deep Learning Engineer – Computer Vision

Full-stack Engineer

• Design, implement, and maintain full‑stack features across frontend, backend services, and data layers.
• Own delivery of well‑scoped components or features, from design through implementation, testing, and production support.
• Contribute to system reliability, performance, and observability improvements by identifying bottlenecks, fixing issues, and following established best practices.
• Collaborate with product managers, designers, and AI research stakeholders to understand user needs and translate them into clear technical solutions.
• Participate in design reviews, code reviews, and on‑call rotations to help maintain a high‑quality, production‑ready system.
• Follow and contribute to team standards for code quality, testing, security, and CI/CD.
• Learn and apply modern practices in cloud infrastructure, deployment, and monitoring with guidance from senior engineers.

Senior Full-Stack Software Engineer

Engineer

• Conduct safety analysis and establish safety concepts to support ongoing and secure software releases
• Collaborate with software developers and AI engineers to ensure safety concepts are implemented and evaluated effectively
• Analyze fleet data, test, and simulation results, providing timely feedback to developers to continuously improve safety
• Help refine processes and tools for analysis and data-driven safety evaluation
• Present safety concepts and safety evaluation results to key collaborators and management to reduce risks to the project

Senior System Safety Engineer – Autonomous Vehicles

• Develop use cases and system requirements for L3 and L4 autonomous driving products based on customer needs, traffic regulations, certification standards, and industry guidelines
• Perform system-level analysis to define performance requirements and allocate performance budgets across subsystems
• Formulate test cases and define critical performance metrics to ensure compliance with functional and safety requirements
• Define and drive online and offline test strategy and execution at both vehicle and component levels
• Partner closely with Data Analytics, Test Engineering, and System Integration & Test teams
• Ensure the right evaluators and important metrics are developed
• Prove that datasets cover sufficient scenarios and requirements
• Target appropriate sampling strategies through Data Collection and Real-World Driving
• Establish strong multi-functional relationships with collaborators across engineering, safety, validation, and product teams
• Drive innovation in requirements decomposition, traceability, and verification processes
• Promote and cultivate a strong systems engineering approach across the organization

Senior Software Systems Engineer, L3 and L4 – Autonomous Driving

• Stay up to date with the latest research and innovations in deep learning, implement and experiment with new ideas
• Foster collaborative partnerships with our researchers and engineers, transforming innovative research into robust, industrial-strength machine learning models
• Taking approaches from initial evaluation and experimentation all the way to shipping
• Defining and collecting training datasets
• Building training pipelines and real-time inference run-times (PyTorch, TensorFlow, TensorRT, Python, C++)

Senior Deep Learning and Computer Vision Engineer – Autonomous Vehicles

• Build innovative world reconstruction systems using large geometry models, perception models, Gaussian splatting algorithms, and generative world models.
• Address user feedback and work to improve the reconstruction fidelity and simulation realism.
• Create evaluation methods to measure the reconstruction quality and tools to visualize and debug issues.
• Profile and optimize the performance of neural networks as well as end-to-end systems.
• Collaborate with researchers and engineers across several organizations.

Senior Computer Vision and DL Engineer – Autonomous Vehicles

• Study and develop state of the art techniques in deep learning, machine learning, and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures
• Provide the best AI solutions using GPUs working directly with key customers
• Collaborate closely with the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and programming models

Developer Technology Engineer, AI

Artificial Intelligence

• Design and scale observability platforms handling high-volume metrics, logs, and traces across distributed environments
• Build high-performance backend services for telemetry ingestion, processing, and routing
• Develop and extend OpenTelemetry collectors, processors, exporters, and instrumentation libraries
• Build and optimize metrics pipelines using large-scale time-series storage systems
• Design and operate real-time and batch telemetry pipelines using streaming and distributed data technologies
• Improve platform reliability, performance, and cost efficiency through tuning, capacity planning, and system optimization
• Develop monitoring, alerting, and service reliability frameworks to ensure platform health and performance
• Collaborate with platform engineering, infrastructure, and site reliability teams to deliver production-grade observability solutions

Senior AI and HPC Observability Engineer

Machine Learning Engineer

• Continuously keeping up to date on the latest advancements in generative AI research.
• Analyzing and prototyping emerging workloads in multi-agent AI systems, generative multimodal models, and inference-time compute scaling.
• Pioneering and developing optimizations for these workloads across the inference stack to push the boundaries of inferencing quality and speed on NVIDIA systems.
• Collaborating closely with production teams to incorporate the latest advancements into cutting-edge software frameworks.