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ML Engineer, Agentic Systems

ML Engineer building and improving agentic systems powered by LLMs for multimodal video understanding, reasoning, and creative editing tasks at an AI-native video platform. Requires strong production ML experience with transformers, fine-tuning, and experimental rigor.

175k – 275kNew York, NYML EngineeringOnsite

About the role

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

Requirements

  • 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

Benefits

  • Comprehensive medical, dental, and vision plans
  • 401K with employer match
  • Commuter Benefits
  • Catered lunch multiple days per week
  • Dinner stipend every night if you're working late and want a bite! Grubhub subscription
  • Health & Wellness Perks
  • Multiple team offsites per year with team events every month
  • Generous PTO policy

Skills

TransformersLLMsFine-TuningModel AlignmentPost-TrainingMultimodal ReasoningStructured GenerationAgentic SystemsPythonPyTorch

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