Machine Learning Intern - Multimodal Models Generative AI

Overview

• We are now looking for a Machine Learning Intern.
• Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction.
• Today, a self-driving car powered by AI can meander through a country road at night and find its way.
• An AI-powered robot can learn motor skills through trial and error.
• This is truly an extraordinary time — the era of AI has begun.
• Image recognition and speech recognition — GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems.
• The GPU started out as the engine for simulating human creativity, conjuring up the amazing virtual worlds of video games and Hollywood films.
• Now, NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world.
• Just as human imagination and intelligence are linked, computer graphics and artificial intelligence come together in our architecture.
• Two modes of the human brain, two modes of the GPU.
• This may explain why NVIDIA GPUs are used broadly for Deep Learning, and NVIDIA is increasingly known as “the AI computing company.
• What you’ll be doing: Support research and development of large language models and multimodal models.
• Work on model fine-tuning, parameter-efficient training, and architecture exploration.
• Assist with experiments, benchmarking, evaluation, and data analysis.
• Develop prototypes using NVIDIA AI platforms and GPU-accelerated tools.
• Collaborate with researchers and engineers on cutting-edge AI innovation projects.
• Explore opportunities for technical publications and research outputs.
• ​​​ What we need to see: Pursuing BS, MS, or PhD in Computer Science, AI, Data Science, Engineering, Mathematics, or related fields.
• Experience with machine learning / deep learning.
• Strong Python programming skills.
• Familiarity with PyTorch or TensorFlow.
• Good analytical and problem-solving skills.
• Good verbal and written communication skills in English.
• Ways to Stand Out from the Crowd Experience with LLMs, VLMs, multimodal AI, NLP, or generative AI.
• Experience with distributed training or GPU computing.
• Interest in applied research and publications.