AI Engineer to Fine‑Tune Sentiment Model for Reviews
Skills Required
Description
Understanding how customers feel about products and services is essential for growth. This project is about fine-tuning a sentiment analysis model to process large volumes of reviews accurately.
The engineer will work primarily with Python and NLP libraries, applying deep learning frameworks such as TensorFlow to adjust the existing architecture.
Data cleaning will be a core part of the job. Raw review data often contains noise, misspellings, and emojis that must be standardized before training.
Pandas will be used heavily for preprocessing. Structured datasets should be prepared with clear labeling to ensure reliable results.
Some reviews may be multilingual. Handling these cases gracefully will be part of the challenge.
The project will focus on both binary sentiment (positive vs. negative) and more nuanced scales, such as star ratings.
Model evaluation will require careful planning. Accuracy alone won’t be enough—precision, recall, and F1 scores will guide progress.
Hyperparameter tuning should be approached systematically. The engineer should run multiple experiments to find the balance between performance and efficiency.
Responsibilities will include:
Preprocessing large review datasets
Fine-tuning deep learning models for sentiment detection
Evaluating models using appropriate metrics
Documenting results and methods clearly
Deployment-readiness will be im...