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.