
Deep Learning Scientist Intern, LLM, Multimodal and Agentic AI - Summer 2027
Santa Clara, CAFull-time$20–94/hrPosted 1 day agoStill listed today
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Job overview
The Deep Learning Scientist Intern will research, design, and develop large language models, multimodal foundation models, and agentic AI systems. The work applies machine learning and deep learning across language, vision, speech, audio, and video, including model training and evaluation, dataset development, and prototyping architectures and inference techniques. The role collaborates with researchers and engineers to scale successful ideas.
Skills & qualifications
Skills
Qualifications
Full job description
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and build our teams with the smartest people in the world. Would you like to join us at the forefront of technological advancement?
Join our team and help build the next generation of large language models, multimodal foundation models, and agentic AI systems. Intelligent machines powered by AI that can understand, reason, plan, interact with people, and take actions are no longer science fiction. Today, LLMs and multimodal models can process and generate text, vision, speech, audio, and video, while increasingly using tools and interacting with complex environments to solve real-world tasks. This is truly an extraordinary time. The era of AI has begun.
What you'll be doing: As a Deep Learning Scientist Intern, you will work on research, design, and development of large language models, multimodal LLMs, and agentic AI systems. You will use machine learning and deep learning techniques across language, vision, speech, audio, and video to develop and improve next-generation foundation models.
- 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, preference optimization, reinforcement learning, and related post-training techniques.
- Develop and evaluate capabilities including reasoning, multimodal understanding, planning, tool use, conversational interaction, and multi-step task completion.
- Build and curate high-quality datasets and evaluation benchmarks for model training, post-training, and performance analysis.
- Prototype new model architectures, algorithms, training strategies, and inference techniques, and collaborate with researchers and engineers to scale successful ideas.
What we need to see:
- Pursuing an MS or PhD degree 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, vision-language models, or multimodal models, with an emphasis on reinforcement learning for agentic reasoning, planning, tool use, and coding.
- Excellent programming skills in Python and experience with deep learning frameworks such as PyTorch, NeMo, Megatron-LM, TensorFlow, or related frameworks.
- Experience developing, training, fine-tuning, or evaluating deep learning models, including familiarity with data processing, dataset development, experiment tracking, and model evaluation workflows.
- Strong problem-solving skills and a demonstrated ability to rapidly prototype, experiment, and evaluate new ideas.
Ways to stand out from the crowd:
- Experience with large language models, multimodal foundation models, vision-language models, or agentic AI research and development.
- Background with post-training techniques such as instruction tuning, preference optimization, RLHF, RLVR, GRPO, or related reinforcement learning methods.
- Experience with multimodal reasoning across text, image, video, speech, or audio, including conversational or audio-language models.
- Experience with reasoning, planning, tool use, function calling, or multi-step agentic systems.
- Background with large-scale model training, distributed frameworks such as NeMo or Megatron-LM, GPU computing, or inference technologies such as vLLM or TensorRT-LLM.
NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most brilliant and talented people in the world working for us. If you're creative and autonomous, with a genuine passion for large language models, multimodal AI, and agentic systems, we want to hear from you!
Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The expected hourly rate for this position is 20 USD – 94 USD. You will also be eligible for Intern benefits.
Applications for this job will be accepted at least until November 8, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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 this job compares
Set against the 545 open Machine Learning Researcher jobs on Olive Jobs, counted November 5, 2026.
- Pay
- This posting$20–94/hr
- California median$58–85/hr20 hourly ranges
- US median$58–85/hr23 hourly ranges
This range's midpoint, $57/hr, is 14% below the California median midpoint ($66/hr) — in the lowest quarter of Machine Learning Researcher hourly ranges in California.
- Openings
- Olive Jobs lists 263 open Machine Learning Researcher jobs in California and 545 across the US. 7% of them nationwide are listed as remote or flexible.
- Experience
- Machine Learning Researcher postings that state a minimum ask for 3 years of experience at the median; the middle half ask for 2 to 5 years (210 postings).
- Education
- 229 of the 545 open Machine Learning Researcher jobs (42%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 5, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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