NVIDIAAI Research Intern, TAO Multi-Modal Model Development - 2026
NVIDIA is hiring an AI Research Intern, TAO Multi-Modal Model Development - 2026 in Hanoi, Vietnam. Level rates it ; you can apply on NVIDIA.
Level's read on this job
- On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include PyTorch, Python and Tao Toolkit.
- Level classifies it as an internship.
- Level lists 2,700+ other open roles at NVIDIA.
AI in this role
Develops and fine-tunes multi-modal AI and vision-language models within the TAO framework.
Our team is seeking to extend the internship of our current AI Research Intern for the TAO (Train, Adapt, Optimize) Multi-Modal Model Development project, recognizing their exceptional performance and strong alignment with the team’s research goals. Their innovative ideas and technical contributions have significantly enhanced our work. Given the rapidly evolving field of multi-modal AI, encompassing vision-language modeling, universal segmentation, and large-scale model training, extending this internship will provide further growth opportunities for the intern while strengthening our team’s capacity to develop scalable, high-impact AI solutions.
Embark on an exciting journey with NVIDIA, a global leader in AI and accelerated computing. As an AI Research Intern focusing on multi-modal AI and vision-language model development within the TAO framework in Hanoi/HCM City, Vietnam, you will be at the forefront of advancing cutting-edge machine learning research. You’ll collaborate with a talented team of engineers and researchers dedicated to developing state-of-the-art deep learning models for tasks such as image segmentation, cross-modal understanding, and universal representation learning. This internship offers a unique opportunity to contribute to next-generation AI systems with real-world impact across industries—from autonomous vehicles to intelligent content understanding.
What you'll be doing:
Develop and fine-tune multi-modal AI models using NVIDIA’s TAO Toolkit and deep learning frameworks.
Contribute to the design and implementation of vision-language models (VLMs) and universal segmentation systems.
Conduct experiments and benchmarking to evaluate model accuracy, robustness, and scalability.
Collaborate with cross-functional teams to integrate your research into production-level pipelines and NVIDIA SDKs.
Participate in research discussions, code reviews, and technical documentation to share insights and improve methodologies.
What we need to see:
Currently pursuing a degree in Computer Science, Computer Engineering, or a related field.
Proven experience with machine learning, deep learning, or computer vision model development.
Strong Python programming skills and proficiency with PyTorch or similar frameworks.
Solid understanding of neural network architectures, transformers, and multi-modal learning techniques.
Excellent problem-solving abilities, attention to detail, and a collaborative mindset.
Familiarity with vision-language models, image segmentation, or large-scale pretraining is a strong plus.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
How we rate this
AI Research Intern, TAO Multi-Modal Model Development - 2026 at NVIDIA rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where deep learning was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where vision language models was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Computer vision, AI Research, Deep learning, Machine learning, and Vision Language Models. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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