Research Scientist / Engineer — Multimodal Agent

• Modeling: Architect large-scale multimodal agentic models that use reasoning, planning, coding, and tool calling to achieve complex, multi-step multimodal work.
• Data: Hillclimbing existing tasks and formulating new tasks through data. Design, implement, and run robust data pipelines for constructing, enriching, and filtering massive pixel datasets.
• Systems: Train large-scale multimodal models on massive datasets and GPU clusters.
• Evaluation: Define and build novel evaluation frameworks to measure multimodal agents.

• Strong foundation in machine learning, foundation models and agentic systems.
• Deep understanding of agentic systems and approaches in LLM/VLM reasoning, coding models, LLM/VLM tool calling.
• Hands-on experience with PyTorch and large-scale training (distributed, mixed precision, large datasets).

• State-of-the-art foundation models in reasoning
• State-of-the-art foundation models in coding
• State-of-the-art foundation models in tool calling
• State-of-the-art multimodal agents

Compensation

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