Senior Multimodal AI Scientist — Agentic Reasoning & LLMs

NVIDIA; Santa Clara (CA); On-site; USD 184,000 - 287,500; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA seeks a Senior Deep Learning Scientist in California to drive research in multimodal AI for agentic systems and foundational models. You will develop language-processing models with multimodal capabilities, advancing RL methods and alignment, and contribute to Nemotron LLM projects.

Responsibilities include data collection, benchmarking, and collaboration across teams to scale models for real-world tasks while pushing the state of the art in AI research.

Qualifications

• Master’s degree or PhD in Computer Science, AI, or Applied Math with 8+ years of relevant work experience.
• Excellent programming skills in Python with scalable model development and PyTorch experience.
• Strong knowledge of ML/DL techniques and modern foundation model architectures (Transformers, MoE).
• Foundational understanding of reinforcement learning algorithms (MDPs, policies, rewards).
• Hands-on experience with post-training multimodal models for audio-visual reasoning and human-AI interaction.

Responsibilities

• Apply research to develop, train, fine-tune, and deploy advanced neural networks for language processing in agentic systems.
• Advance post-training and alignment methods including instruction tuning and RLHF/RLVR for multimodal agents.
• Research agentic reasoning and grounded perception for planning and long-horizon tasks across digital and physical environments.
• Lead collection and benchmarking of multimodal datasets with high-quality evaluation.

Skills

Python

PyTorch

Transformers

Mixture-of-Experts

Reinforcement Learning

Education

Master’s degree

PhD

Tools

PyTorch

Job description

NVIDIA seeks a Senior Deep Learning Scientist in California to drive research in multimodal AI for agentic systems and foundational models. You will develop language-processing models with multimodal capabilities, advancing RL methods and alignment, and contribute to Nemotron LLM projects.

Responsibilities include data collection, benchmarking, and collaboration across teams to scale models for real-world tasks while pushing the state of the art in AI research.