Research Engineer, Agentic Systems

Responsibilities

Design and build end-to-end agentic systems for creative tasks
Develop novel approaches for training and adapting the large language models that power these agents
Design new objectives, datasets, and fine-tuning strategies to improve agent behavior and reliability
Explore multimodal reasoning and structured generation for creative control
Run systematic experiments to evaluate and improve agent performance in real-world tasks
Design evaluation frameworks for agentic workflows in video analysis and editing
Analyze failure modes across the full agent loop (planning, tool use, execution) and iterate on improvements

What makes you a great fit

BS/MS/PhD in CS, ML, or related field
Strong track record building production ML systems or agentic pipelines
Deep understanding of transformers and modern LLM techniques
Experience with fine-tuning, alignment, or post-training methods, especially for adapting models to generate structured outputs or drive tool use
Comfort owning the full stack, from model-level experiments to deployed agent systems
Strong experimental rigor and good taste for what makes agents actually work in practice