Multimodal AI Research Scientist: Agentic Models

lumalabs-ai; San Francisco (CA); On-site; USD 250,000 - 450,000; Full time

Job summary

Luma AI seeks to define the future of multimodal AI by building and training large-scale multimodal models. You will join a team that bridges research with shipped products, working end-to-end on novel problems with no existing playbook.

This role blends the science and engineering aspects of research, focusing on modeling, data, systems, and evaluation to advance multimodal agents across big datasets and GPU clusters.

Qualifications

• 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).

Responsibilities

• 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.

Skills

Foundation models

Agentic systems

LLM/VLM reasoning

Large-scale training

Tools

PyTorch

Job description

Luma AI seeks to define the future of multimodal AI by building and training large-scale multimodal models. You will join a team that bridges research with shipped products, working end-to-end on novel problems with no existing playbook.

This role blends the science and engineering aspects of research, focusing on modeling, data, systems, and evaluation to advance multimodal agents across big datasets and GPU clusters.