英伟达MLOps Data Platform Intern, Automotive - 2026

NVIDIA is leading company of AI computing. At NVIDIA, our employees are passionate about AI, HPC , VISUAL, GAMING. Our Solution Architect team is more focusing to bring NVIDIA new technology into difference industries. We help to design the architecture of AI computing platform, analyze the AI and HPC applications to deliver our value to customers. This role will be instrumental in leveraging NVIDIA's cutting-edge technologies to optimize open-source and proprietary large models, create AI workflows, and support our customers in implementing advanced AI solutions.  What you’ll be doing: • Drive the implementation and deployment of NVIDIA Inference Microservice (NIM) solutions  • Use NVIDIA NIM Factory Pipeline to package optimized models (including LLM, VLM, Retriever, CV, OCR, etc.) into containers providing standardized API access • Refine NIM tools for the community, help the community to build their performant NIMs  • Design and implement agentic AI tailored to customer business scenarios using NIMs • Deliver technical projects, demos and customer support tasks • Provide technical support and guidance to customers, facilitating the adoption and implementation of NVIDIA technologies and products  • Collaborate with cross-functional teams to enhance and expand our AI solutions

The Role We are looking for a highly motivated intern specializing in platform security to defend Tesla’s information, infrastructure, and products. The platform Security team is responsible for helping Tesla securely design, build, and operate infrastructure across corporate, manufacturing and production environments. As an Information Security Engineer you will work on a broad set of efforts including: engineer repeatable security controls to defend Tesla's manufacturing environments, defending systems and users against attacks, and implementing technology and architecture to scale security globally. On the same time,we need to focus on cloud security management too. For example, account abuse, data flow expose,  etc. As in China we have more and more cyber security regulation and law enforcement, we need you to know well these regulations and understand well how to cooperate with MIIT and cyber security policy in China for MLPS and other certification Responsibilities Analyze security data and report on infrastructure security status across environments. Management cloud security Help to pass MLPS for all these core system of Tesla China New project architecture cyber security assessment

• You will master one or more subareas and gain expertise in a broad area of research, including applicable research techniques. You’ll also gain deep knowledge of a service, platform, or domain, and identify product needs by sharing the latest industry trends and applied technologies.  • You will review business requirements and incorporate research to meet business goals. You’ll provide strategic direction for the kinds of data used to solve problems and apply deep subject matter knowledge to support business impact.  • You will participate in onboarding of junior team members and assist in developing academics to be members of multidiscipline teams. You’ll identify new research talent to join Microsoft and collaborate with the academic community to develop the recruiting pipeline.  • You will document work in progress and experimentation results and share findings to promote innovation. You’ll also use your deep understanding of fairness and bias to contribute to ethics and privacy policies related to research processes and data collection. 

• Lead hands-on design and development efforts primarily using Python, building robust, scalable, and customer-focused AI/ML solutions. • Engage directly with key enterprise customers to strategize, architect and implement AI driven, Agentic AI solutions leveraging Azure AI services including Azure OpenAI, Azure ML. • Translate complex requirements into practical, well-architected technical solutions. • Develop end-to-end, rapid prototypes, involving data ingestion, validation, processing, and model deployment using Azure platform components. • Build, customize, and optimize AI models and related components for customer-specific use cases. • Integrate AI solutions with full-stack architectures, preferably leveraging experience with JavaScript frameworks (e.g., Node.js, React) and/or .NET ecosystems. • Establish and maintain robust CI/CD and ML Ops pipelines, leveraging Azure DevOps, Github for automated deployments. • Proactively explore diverse datasets to engineer novel features and signals that significantly enhance ML performance. • Participate actively in every phase of the model lifecycle from conceptualization, training, fine tuning, validation, and deployment, to continuous monitoring and improvement.