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Mirage is an AI-native video platform that uses natural language to orchestrate production and editing, leveraging models that replicate professional editor decisions. The company is backed by top-tier investors including Sequoia, Andreessen Horowitz, Kleiner Perkins, and Index Ventures, and was recently featured in Forbes AI 50 and Fast Company's Most Innovative Companies.
As a Research Engineer focused on Agentic Systems, you will design and build end-to-end agentic systems for creative tasks, developing novel approaches for training and extending large language models that operate over complex, real-world video data. Your work will advance agent capabilities, improve reasoning and control, and enable new forms of interaction between language models and time-based media.
Key responsibilities include:
- Designing and building end-to-end agentic systems for creative tasks
- Developing novel training and adaptation approaches for large language models powering these agents
- Creating new objectives, datasets, and fine-tuning strategies to improve agent behavior and reliability
- Exploring multimodal reasoning and structured generation for creative control
- Running systematic experiments to evaluate and improve agent performance in real-world tasks
- Designing evaluation frameworks for agentic workflows in video analysis and editing
- Analyzing failure modes across the full agent loop (planning, tool use, execution) and iterating on improvements
You should have a BS/MS/PhD in CS, ML, or related field, with a strong track record building production ML systems or agentic pipelines. Deep understanding of transformers and modern LLM techniques is essential, along with hands-on experience in fine-tuning, alignment, or post-training methods—particularly for adapting models to generate structured outputs or drive tool use. You'll own the full stack from model-level experiments to deployed agent systems, with strong experimental rigor and practical intuition for what makes agents work in production.
