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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.