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.
• Research post-training, alignment, and reinforcement-learning methods to improve multimodal agent capabilities.
• Lead multimodal dataset development and benchmarking for accuracy, safety, and task completion.

What they ask for

• Master’s degree (or equivalent experience) or PhD in Computer Science, AI, or Applied Math.
• 8+ years of relevant work experience.
• Strong Python programming, scalable model development, and deep learning framework skills, including PyTorch.
• Hands-on experience post-training multimodal models for audio-visual reasoning, full-duplex voice chat, and human-AI interaction.

Nice to have

• Strong publication record in top-tier AI/ML venues such as NeurIPS, ICML, ICLR, or CVPR.
• Experience with large-scale distributed multimodal model training, deep RL for agents, audio/speech AI, or embodied AI.

Pay

184,000 USD - 287,500 USD base salary

Tools

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

AI focus

Research and develop multimodal agentic AI, including foundation-model post-training and alignment, reinforcement learning, grounded perception, planning, tool execution, and long-horizon task completion.