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Mirage

Research Engineer, Agentic Systems

Union Square, New York City$175k–$300kfulltimemidAdded today

About this role

Mirage seeks an ML Engineer to develop agentic systems that enable AI-driven video production and editing through natural language. You'll advance LLM capabilities for multimodal creative tasks, design novel training approaches, and build end-to-end agent systems that understand and manipulate video content.

What you'll do

  • Design and build end-to-end agentic systems for creative video tasks
  • Develop novel training and adaptation approaches for large language models powering agents
  • Create datasets, objectives, and fine-tuning strategies to improve agent behavior and reliability
  • Explore multimodal reasoning and structured generation for creative control over video
  • Run systematic experiments to evaluate agent performance on real-world video workflows
  • Analyze failure modes across planning, tool use, and execution loops to iterate improvements

What they're looking for

  • Large language models and transformer architectures
  • Agentic systems and agent design patterns
  • Fine-tuning, alignment, and post-training methods
  • Structured output generation and tool use
  • Multimodal reasoning (text, vision, video)
  • Experimental design and evaluation frameworks
  • Production ML systems and deployment
  • Video analysis and understanding

Benefits

  • Comprehensive medical, dental, and vision coverage
  • 401(k) with employer match
  • Catered lunch multiple days per week
  • Dinner stipend for late-night work
  • Grubhub subscription and wellness perks
  • Generous PTO and multiple team offsites annually
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Mirage

Mirage builds an AI-native video platform that leverages generative media and large language models to enable sophisticated video production, editing, and creative workflows. The company is hiring backend engineers, full-stack software engineers, ML engineers, and iOS developers to advance their AI-driven platform and enhance user experiences in web-based and mobile media creation.

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Likely interview questions

  • Describe a production agentic system you've built—how did you design the agent loop and handle failure modes?
  • What techniques have you used to fine-tune LLMs for tool use or structured output generation, and how did you measure success?