Senior Deep Learning Scientist, Multimodal Agentic RL - US, CA, Santa Clara
$184,000 - $287,500 USD yearly
Originally posted 2 October 2026 by the employer.
This role focuses on advancing multimodal foundation models, scaling ideas through Nemotron Omni and VoiceChat platforms.
About the role
This role involves advancing NVIDIA's efforts in streaming and agentic multimodal AI. You will help develop models capable of reasoning, planning, and acting across diverse modalities, scaling ideas through Nemotron Omni and VoiceChat platforms.
What you'll do
- Apply fundamental and applied research to develop, train, fine-tune, and deploy large language models for agentic systems encompassing audio-visual reasoning, tool usage, and document understanding.
- Advance post-training and alignment methods including instruction tuning, preference optimization, and RLHF/RLVR/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.
What you'll need
- Master’s degree (or equivalent experience) or PhD in Computer Science, AI, or Applied Math with 8+ years of relevant work experience.
- Excellent programming skills in Python with strong fundamentals in scalable model development and deep learning frameworks like PyTorch.
- Strong knowledge of ML/DL techniques and modern foundation model architectures, including Transformers and mixture-of-experts models.
- Foundational understanding of reinforcement learning algorithms and implementation, including MDPs, policies, and reward design.
- Hands-on experience in 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.
Skills: Deep Learning Scientist, Multimodal Agentic RL, foundation models, LLMs, reinforcement learning, PyTorch
This role has been open 2 days — well below the 75-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
501
|
Median days open
75 d
|
Median salary
$232k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | NVIDIA | All employers we track in this specialty (501 roles · 75 employers) |
|---|---|---|
| Open roles in this specialty | 84 | 501 |
| Open roles in the wider Software, Firmware & Systems family | 949 | 5938 · 145 employers |
| Median days open | 71 d | 75 d (−4 d vs this employer) |
| Median salary (USD postings) | — | $232k |
Skills observed across this category: Deep Learning Scientist, Multimodal Agentic RL, foundation models, LLMs, reinforcement learning, PyTorch
Who's hiring in this category
- Qualcomm · 99 open roles · median 108 d
- NVIDIA (this employer) · 84 open roles · median 71 d
- AMD · 42 open roles · median 65 d
- Micron Technology · 30 open roles · median 57 d
- Mobileye · 20 open roles · median 72 d
- NXP Semiconductors · 15 open roles · median 62 d
How we counted: 501 open AI/ML Hardware Engineering (AI ML Hardware) roles from 75 employers tracked in the SemiconductorJobs index, counted 5 Oct 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.