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AI Sentiment Analysis Engineer

Amelia Weber

Part-time · Job · New_York

About the role

Our clients — PR agencies and brand managers — need to know what people are saying about their brands, and whether the tone is positive, negative, or neutral. Sounds simple. It's not. Sarcasm, irony, context-dependent meaning, and brand-specific vocabulary make general sentiment models nearly useless for professional brand monitoring. This part-time role (20h/week) focuses on improving our domain-specific sentiment models. You'll fine-tune Hugging Face models on brand monitoring datasets, build evaluation frameworks that capture the nuances general accuracy metrics miss, and help maintain the annotation pipeline that keeps our training data current. Ideal for a student or early-career NLP engineer who wants hands-on experience with real production models while maintaining schedule flexibility.

Responsibilities

  • Fine-tune sentiment classification models on brand monitoring datasets
  • Build evaluation frameworks capturing sarcasm and context-dependent sentiment
  • Maintain and improve the annotation pipeline for training data quality
  • Analyze model performance across different industries and brand contexts
  • Document model improvements and evaluation methodology

Requirements

  • Python proficiency with Hugging Face and PyTorch basics
  • Understanding of NLP fundamentals and text classification
  • Familiarity with sentiment analysis concepts and challenges
  • SQL skills for querying text databases
  • Available for 20 hours/week

Benefits

  • Part-time (20h/week) with flexible scheduling
  • Fully remote
  • Mentorship from senior NLP engineers
  • Option to transition to full-time

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Categories

NLP & Prompt Engineering data science & analytics

Skills

python hugging face pytorch pandas sql

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Salary Range

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AI Expertise

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Skills

python hugging face pytorch pandas sql statistics

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