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AI Editing

Research Engineer, Agentic Systems

Mirage

External listing
Union Square, New York CityUnknownFull-time$175,000–$275,000/year
External listing from the employer

Originally published by Mirage through its Ashby careers source. Applications go to the employer's website, and AIMovieJobs is not the hiring employer.

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Quick facts

Union Square, New York CityLocationUnknownWorkplaceFull-timeJob type$175,000–$275,000/yearCompensationAI EditingCategoryEngineeringDepartmentAug 31, 2026PostedSep 8, 2026Last verifiedMar 7, 2027Expires

Role overview

As an early member of our team, you’ll tackle foundational problems that remain largely unsolved across the industry, driving an outsized impact on the future of creative expression. You'll develop new approaches for building and extending agentic systems that understand and operate over complex, real-world data, particularly video. ResponsibilitiesDesign and build end-to-end agentic systems for creative tasksDevelop novel approaches for training and adapting the large language models that power these agentsDesign new objectives, datasets, and fine-tuning strategies to improve agent behavior and reliabilityExplore multimodal reasoning and structured generation for creative controlRun systematic experiments to evaluate and improve agent performance in real-world tasksDesign evaluation frameworks for agentic workflows in video analysis and editingAnalyze failure modes across the full agent

What you'll do

  • 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