AI Research Intern at NVIDIA focusing on multi - modal AI and vision - language model development. Collaborating with engineers to advance cutting - edge machine learning research in Vietnam.
About the role
- Apply research ideas to real-world scenarios under the guidance of experienced mentors.
- Conduct research on novel and existing AI paradigms to address defined problem statements.
- Design and develop high-quality software frameworks and tools for end-to-end AI lifecycles.
- Manage data collection, calibration, and model development for reliable, scalable performance.
- Implement, test, and optimize AI models or agentic workloads for real-time applications.
- Communicate results and insights through reports, presentations, papers, or patents.
- Collaborate across teams to ensure solutions align with deployment, cost, and performance goals.
Requirements
- AI/ML fundamentals and algorithms: learning strategies, feature engineering, generalized and specialized models
- Full-stack programming: Python, version control, dashboard, scripting, AI/agentic frameworks
- DevOps for AI/ML lifecycle: Kubernetes, continuous deployment, and training
- The ability to interpret and communicate key underlying ideas, concepts, and associated problems in complex research papers and system reports.
- Willingness to contribute with creative, out-of-the-box solutions, to problems arising in a dynamic environment
- It would be nice if you also had knowledge or experience of one or more of the following:
- Learning architectures, ML model optimization, model drift detection, lifetime learning, knowledge graphs, or world models
- Developing solutions using single or multi-modal data (e.g., vision, text, RF) combined with machine learning to solve interesting problems.
- Wireless or wireline connectivity fundamentals, such as communication theory, networking, or interconnect fundamentals.
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