Senior Deep Learning Scientist, Multimodal Agentic RL

at Nvidia

USD 184,000-287,500 per year

SENIOR

✅ On-site

Tech Stack
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1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 4 Agentic Systems @ 4 Algorithms @ 4 Deep Learning @ 7 LLM Machine Learning @ 7 Mathematics @ 7 PyTorch @ 7 Python @ 7 Reinforcement Learning @ 4

Details

NVIDIA is hiring Senior Deep Learning Scientists to advance streaming and agentic multimodal AI. The role focuses on developing models capable of reasoning, planning, and acting across diverse modalities, including large language models and multimodal AI products built on the Nemotron Omni and VoiceChat platforms.

Responsibilities

Apply fundamental and applied research to develop, train, fine-tune, and deploy large language models for agentic systems involving audio-visual reasoning, tool usage, and document understanding.
Advance post-training and alignment methods, including instruction tuning, preference optimization, RLHF, RLVR, and MOPD, to improve multimodal agents for complex use cases.
Research and develop agentic reasoning and grounded perception capabilities, focusing on planning, tool execution, and long-horizon task completion across digital and physical environments.
Lead the collection, development, and benchmarking of multimodal datasets, ensuring high-quality evaluation of model accuracy, safety, and task-completion success.

Requirements

Master's degree or equivalent experience, or PhD, in Computer Science, Artificial Intelligence, or Applied Mathematics, with 8+ years of relevant work experience.
Excellent programming skills in Python, with strong fundamentals in scalable model development and deep learning frameworks such as PyTorch.
Strong knowledge of machine learning and deep learning techniques and modern foundation model architectures, including Transformers and mixture-of-experts models.
Foundational understanding of reinforcement learning algorithms and implementation, including Markov decision processes, policies, and reward design.
Hands-on experience post-training multimodal models for omni-modality audio-visual reasoning, full-duplex voice chat, and human-AI interaction.
Proven ability to manage model development life cycles, including dataset versioning, experiment tracking, and evaluation pipelines.

Preferred Qualifications

Strong publication record in top-tier AI and machine learning venues such as NeurIPS, ICML, ICLR, or CVPR.
Experience training and deploying multimodal foundation models using large-scale distributed infrastructure.
Experience applying deep reinforcement learning techniques to train multimodal agents in complex simulation or gaming environments.
Background in audio and speech AI, especially audio language models or audio generation.
Background building embodied AI systems that integrate multimodal perception with backend action fulfillment and long-horizon planning.

Benefits

Equity and benefits are provided.
NVIDIA promotes an inclusive work environment and is an equal opportunity employer.
Applications will be accepted at least until July 31, 2026.