英伟达MLOps Data Platform Intern, Automotive - 2026
任职要求
NVIDIA’s Automotive division is building the next generation of AI and accelerated computing technologies for autonomous driving. Our MLOps Data Platform team designs large-scale data infrastructure powering Ground Truth (GT) generation, sensor fusion, and end-to-end AI workflows for global automotive partners. We are expanding our data platform globally to deliver GT data across regions and support diverse DNN networks for various OEMs.We're looking for a motivated MLOps Data Platform Intern to help build, scale, and optimize this global data ecosystem while driving strong collaboration across engineering, operations, and research teams. What You’ll Be Doing: • Contribute to the development of distributed data pipelines supporting large-scale GT generation and global data distribution. • Support the integration of international datasets (vision, LiDAR, map, and sensor) for multi-region model development and validation. • Assist in automating workflows for data validation, QA, and release, improving throughput and reliability across global operations. • Collaborate with cross-functional teams (MLOps, MLE, Mapping, AI Research, Ops) to ensure consistent delivery of GT data worldwide. • Help design tools for monitoring data quality, job status, and progress tracking within the global GT release pipeline. • Particip…
工作职责
N/A
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
• 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.
The ideal candidate will have experience in customer-facing roles and success in leading in-depth technical Application development architecture discussions with senior customer executives, Architects, IT Management, and Developers to drive value to our customers and is open to travel to customer site as needed by business. • Understanding Customer/Partner Technical Environment (Insights about Customer/Partner and Industry): Gather customer/partner insights (e.g., feedback around technical preferences, environments, business needs, competitive landscape), and map architecture and digital transformation solutions to customer/partner business outcomes. Adapt business models, plans, and solutions to insights. • Understanding Customer/Partner Technical Environment (Internal Advocacy): Act as the voice of the customer (VOC)/partner by driving new feedback, gaps, blockers, insights, resources, etc. across communities to track, add, and prioritize, using established channels (e.g., UAT/TFT). • Architecture Design and Deployment (Architecture Proposals): Receive and synthesize data about customer/partner business and technical requirements, address them with technical architecture(s), demonstrate and prove those solutions capability and business value through design collaboration sessions with the customer/partner. • Architecture Design and Deployment (Requirements and Constraints): Apply broad technical knowledge across various architecture solutions to meet business and information technology (IT) requirements and resolve identified technical constraints. Help to shape and enhance customers' requirements. • Application Development, Architecture Design and Deployment (Resolving Blockers): Identify, escalate, and work to resolve technical blockers (e.g., changing configurations, sample coding) to accelerate architecture implementations and routes non-technical issues for removal by the appropriate party. • Trusted Advisor (Challenger Mindset): Respectfully challenge customers/partners when going in the wrong direction and escalate appropriately. • Trusted Advisor (Competitor Insights/ Differentiated Value Proposition): Understand the competitor's architecture solutions and identify Microsoft's strengths over competitive solutions to drive conversations with customers/partners and convince them of solution. • Customer Usage: Lead architecture design, resiliency reviews, and technical optimization that result in production deployment application and increase customer business value. Drive efforts to ensure that the customer's environment and applications are well-architected. • Customer Satisfaction – Deliver positive Customer Satisfaction and become trusted advisors to customers by leveraging solution area expertise to enable defined Customer Success Plan outcomes.