Deep Learning Scientist Intern: LLMs & Multimodal AI

NVIDIA Corporation; United States; Presencial; USD 28.000 - 129.000; A tiempo parcial

Ventajas ofrecidas por este puesto de trabajo

Intern benefits

Hourly rate

Descripción de la vacante

NVIDIA invites applications for a Deep Learning Scientist Intern to work on research, design, and development of large language models, multimodal foundation models, and agentic AI systems. You will apply machine learning across text, vision, speech, audio, and video to advance next-generation foundation models and their deployment.

Candidates pursuing MS or PhD in CS, EE, AI, or applied math should have strong ML/DL knowledge, experience with transformers, Python, and frameworks like PyTorch or

Formación

• Pursuing an MS or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, Applied Mathematics, or a related field.
• Strong knowledge of machine learning and deep learning techniques, algorithms, and modern foundation model architectures, including Transformers.
• Experience or exposure to large language models, multimodal models, or reinforcement learning for agentic reasoning and tool use.

Responsabilidades

• Research and develop large language models, multimodal foundation models, and agentic AI systems across text, vision, speech, audio, and video.
• Develop, train, fine-tune, and evaluate foundation models using supervised fine-tuning, instruction tuning, and reinforcement learning.
• Prototype new model architectures and training strategies, and collaborate with researchers and engineers to scale ideas.

Conocimientos

Python

PyTorch

Transformers

Deep learning

Reinforcement learning

Educación

MS/PhD candidate in CS/EE/AI

Herramientas

Megatron-LM

NeMo

TensorFlow

Descripción del empleo

NVIDIA invites applications for a Deep Learning Scientist Intern to work on research, design, and development of large language models, multimodal foundation models, and agentic AI systems. You will apply machine learning across text, vision, speech, audio, and video to advance next-generation foundation models and their deployment.

Candidates pursuing MS or PhD in CS, EE, AI, or applied math should have strong ML/DL knowledge, experience with transformers, Python, and frameworks like PyTorch or