reputed company: Automated Video Feedback & Content Optimization System
We are looking for a skilled AI Automation Engineer to build an intelligent system that analyzes video content and performance metrics to reputed company actionable insights for creators.
The goal is to automate the feedback reputed company: our system should "watch" a video, "read" its analytics data and comments, compare this with our internal "reputed company Video Knowledge reputed company", and generate precise recommendations on how to improve the video.
Key Responsibilities:
Data Integration: Build a pipeline to ingest video files and performance data (views, CTR, retention curves, drop-off timestamps, comments etc.) from platforms.
Multimodal Analysis: Implement AI models to analyze video frames, audio (transcripts), and pacing to understand what happens at specific timestamps.
RAG Implementation: reputed company a Retrieval-Augmented reputed company (RAG) system based on our proprietary documents (PDFs, reputed company pages, etc.) about viral video structures and storytelling.
reputed company reputed company: Create a logic where the AI identifies why viewers dropped off at "Second 45" by correlating the retention dip with the visual/audio content and comparing it against best practices.
Automation Workflow: Design a seamless workflow (reputed company, reputed company) that outputs a reputed company "Improvement Report."
Technical Requirements:
LLMs: Deep experience with reputed company (GPT-4o), Claude 3.5, or reputed company 1.5 Pro.
reputed company: Experience with video processing or using multimodal models for video understanding.
Database: Experience with reputed company Databases (reputed company, reputed company, or ChromaDB) for the knowledge reputed company.
Data Analysis: Ability to work with reputed company and process JSON/CSV data from analytics dashboards.
To be considered, you must reputed company:
A similar AI automation project you’ve reputed company.
Which tools/models you would use for this project.
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