We need an experienced Python developer with expertise in web scraping, machine learning, and automation to review, optimize, and run an existing domain crawler. The goal is to improve efficiency, accuracy, and reliability.
This project will be conducted in two stages:
Stage 1: Successfully Run the Existing Crawler Your first task is to set up and successfully run the crawler to validate that you can: - Install and configure all dependencies - Execute the crawler on a dataset of domain names - Generate valid output - Troubleshoot any initial setup issues
Once this is successfully demonstrated, we will move to Stage 2.
Stage 2: Propose a Better Solution or Manage Ongoing Runs - Depending on your expertise and analysis of the current crawler, you will either:
A) Propose & Implement Improvements (Rewrite or Optimize the Crawler) - Identify inefficiencies and suggest a better architecture - Improve performance & accuracy (e.g., async scraping, multiprocessing, better ML model) - Ensure scalability if running on large datasets - Refactor code for long-term maintainability OR B) Run & Maintain the Crawler Monthly - Execute the crawler on a scheduled basis - Monitor accuracy and adjust as needed - Fix bugs & ensure stability - Implement new features & improvements over time - Provide regular reports on data quality and insights
About the current crawler The current crawler is built in Python and classifies domain names based on their content (e.g., parked, active, expired). It utilizes: - Requests / Aiohttp (Web scraping) - Selenium (Browser automation) - BeautifulSoup (HTML parsing) - Langdetect / NLP (Language detection & text classification) - XGBoost (Machine learning classification)
Ideal Candidate: - Strong Python skills (async programming, OOP) - Web scraping & automation expertise (requests, Selenium, BeautifulSoup) - Machine learning experience (XGBoost, Scikit-learn, NLP) - Familiarity with databases (SQL/NoSQL) for storing results - Cloud/DevOps experience (if needed for large-scale deployment) - Ability to work independently and ensure high-quality results - High level in English
Project Timeline & Budget: Deliverables expected within 2-4 weeks Budget: Open to discussion based on experience & estimated work required.
Multimodal Emotion Recognition Development Category: Data Science, Machine Learning (ML), Multimodal Large Language Model, Natural Language Processing Budget: ₹12500 - ₹37500 INR
