Machine Learning Engineer

Project 1: Boutique Partnership Dataset

Objective

Build a high-quality database of independent clothing boutiques and fashion brands in:

• The Netherlands
• Delhi, India

These boutiques will be evaluated as potential partners for collecting garment and fit-related data that will support the development of Rhyoms platform.

Responsibilities

• Develop scripts or workflows to collect business information from publicly available sources such as:
• Google Maps
• Boutique websites
• Instagram
• Business directories
• Identify independent clothing boutiques and apparel brands.
• Extract, clean, and validate business information.
• Build a structured dataset containing:
• Business name
• City
• Website
• Contact email
• Phone number
• Instagram/social media
• Contact person (if available)
• Clothing category
• Notes on partnership suitability
• Remove duplicate and inaccurate records.
• Document your data collection methodology.
• Prepare a reusable outreach message template.

Deliverables

• Structured spreadsheet/database of candidate boutiques.
• Verified contact information.
• Documented data collection workflow.
• Prioritized shortlist of recommended boutique partners.
• Draft outreach message template.

Project 2: Clothing Fit Complaint Dataset

Objective

Build a structured dataset of real user complaints related to clothing fit, sizing, and product quality, categorized by issue type to support future fit-filtering and machine learning models.

Potential Data Sources

• Trustpilot (Clothing Store category)
• Sitejabber
• Reddit
• Other publicly available review platforms (where permitted)

Responsibilities

• Review each sources robots.txt, Terms of Service, and scraping policies before collecting data.
• Identify relevant clothing brands and retailers to target.
• Develop scraping pipelines to collect:
• Review text
• Rating
• Review date
• Brand/store name
• Clean and preprocess review data.
• Identify and tag reviews containing fit-related issues, including (but not limited to):
• Size runs too small
• Size runs too large
• Inconsistent sizing
• Poor fit
• Fabric quality
• Material durability
• Shrinkage after washing
• Stitching or manufacturing defects
• Other clothing quality issues
• Design a consistent tagging schema that can be expanded in future projects.
• Document assumptions, limitations, and data sources.

Deliverables

• A structured dataset (CSV and/or JSON) containing fit-related complaints.
• Tagged issue categories for each review.
• Associated brand/store information.
• Data collection and preprocessing scripts.
• Documentation describing the scraping process, tagging methodology, and dataset schema.

Required Skills

• Strong Python programming skills.
• Experience with web scraping and data collection.
• Experience with:
• BeautifulSoup
• Selenium or Playwright
• Requests
• Pandas
• Experience cleaning and validating datasets.
• Familiarity with JSON and CSV data formats.
• Knowledge of web scraping ethics, robots.txt, and Terms of Service considerations.
• Proficiency with Excel or Google Sheets.
• Strong attention to detail.
• Ability to write clean, maintainable, and well-documented code.

Nice to Have

• SQL
• API integration experience
• ETL or data engineering experience
• NLP or text classification experience
• Experience working with review datasets or sentiment analysis
• Familiarity with retail, fashion, or e-commerce datasets

Ideal Candidate

We’re looking for someone who enjoys collecting, cleaning, and structuring data from multiple online sources. You should be comfortable building reliable scraping pipelines, handling messy real-world data, and thinking critically about data quality. Experience with text data and preparing datasets for downstream machine learning tasks is a strong advantage.

Duration

• Project-based (approximately 2–3 weeks)
• Remote
• Flexible working hours

Opportunity for Full-Time Role

This project is intended to identify someone who can grow with the company. Candidates who deliver high-quality work, demonstrate strong programming skills, write maintainable scraping pipelines, and take ownership of the project will be considered for a full-time Machine Learning Engineer role at Rhyom.

In the full-time role, you will contribute to building scalable data pipelines, preparing training datasets, developing machine learning models, and creating intelligent features that improve the clothing shopping experience on Rhyom’s platform.