Senior Deep Learning Scientist, Multimodal Agentic RL

What you'll do

• Develop, train, fine-tune, and deploy large language models for agentic systems, including audio-visual reasoning, tool use, and document understanding.
• Advance multimodal post-training and alignment methods, and develop agentic reasoning, grounded perception, planning, and long-horizon task completion.
• Lead multimodal dataset development and benchmarking for model accuracy, safety, and task success.

What they ask for

• Master’s degree (or equivalent experience) or PhD in Computer Science, AI, or Applied Math.
• Strong Python programming skills and experience with scalable model development and deep learning frameworks such as PyTorch.
• Knowledge of ML/DL, foundation model architectures including Transformers and mixture-of-experts, and reinforcement learning fundamentals.
• Hands-on experience post-training multimodal models for audio-visual reasoning, full-duplex voice chat, and human-AI interaction; ability to manage model development lifecycles.

Nice to have

• Publications in top-tier AI/ML venues such as NeurIPS, ICML, ICLR, or CVPR.
• Experience with large-scale multimodal model deployment, deep RL for agents, audio/speech AI, or embodied AI systems.

Pay

152,000 USD - 241,500 USD base salary (Level 3); 184,000 USD - 287,500 USD base salary (Level 4)

Tools

Python, PyTorch, Transformers, mixture-of-experts, RLHF, RLVR, MOPD, Nemotron Omni

AI focus

Research and build multimodal agentic AI, including audio-visual reasoning, tool use, planning, alignment, reinforcement learning, and long-horizon task completion.