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 – 275k
On-siteML Engineering
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
Build and ship end-to-end agentic systems and architectures for creative video workflows at an AI-native video platform. Requires 5+ years building production ML/agentic pipelines, deep RAG/context engineering experience, and strong evaluation skills.
175k – 275k
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