Verified Job
Internet
Vibecode Specialist - Web Scraping & Data Extraction
Internet
#759416
Remote / WFH
OpenTrain AI
Job Description
About OpenTrain AI
OpenTrain AI is the #1 platform for finding and building careers in AI training and data labeling. We connect skilled contributors with technical annotation and data-prep work that directly shapes how modern AI systems behave.
We hire and contract contributors directly. This role is an OpenTrain AI position, offered as a flexible, remote contract so you can build a technical portfolio while working around your schedule.
Why AI training and data labeling matter
AI training (also called data labeling or human feedback work) is the human side of building artificial intelligence: people prepare, review, and validate the examples models learn from. This work is highly accessible, often remote and flexible, and places contributors on the cutting edge of the field.
As a Vibecode Specialist you’ll work in a hybrid AI+human setup where AI agents automate repetitive steps and you provide quality control, troubleshooting, and critical thinking to produce high-quality training data for fine-tuning and evaluation tasks.
The role
You will own end-to-end web scraping and data-extraction workflows to produce clean, validated structured datasets from complex websites. Tasks combine hands-on coding, practical data engineering, and quality review.
Work is remote and global. Expect approximately 20+ hours per week in a contract, part-time arrangement paid at $20 USD per hour.
• Data type: Text (unlabeled source content; you will extract and normalize fields).
• Labeling focus includes coding/programming work, fine-tuning data preparation, and evaluation/rating of extracted outputs.
• You will use internal tools and your own scripts (examples: Apify, OpenRouter, Playwright/Selenium, custom Python).
What you'll do day-to-day
Deliver robust scraping workflows, validate outputs, and hand off clean CSV/JSON/Google Sheets. Troubleshoot failures and adapt when site structures change.
• Design and implement Python-based scrapers for dynamic, JavaScript-rendered sites (BeautifulSoup + Selenium/Playwright or equivalents).
• Extract multi-level site content (category → entity → details) and normalize fields to specification.
• Implement resilient scraping strategies: selector fallbacks, retries, rate controls, and error handling.
• Scale work via batching, parallelization, or other performance approaches to handle large jobs.
• Use LLMs/AI tools to accelerate extraction, prompting, or data-cleaning steps and evaluate their outputs.
• Document edge cases, follow detailed specs, and produce reproducible deliverables (CSV/JSON/Sheets).
Requirements
You must meet every stated requirement below to be considered. We do not require prior labeling platform experience, but you must be technically hands-on with scraping and data pipelines.
• 1+ year experience in at least one: web scraping, data engineering, software development, automation, or data analysis.
• Strong Python web scraping skills (e.g., BeautifulSoup plus Selenium or Playwright, or equivalent toolsets).
• Proven experience scraping dynamic/JS-heavy sites (infinite scroll, AJAX, JS-rendered content).
• Experience extracting from multi-level/hierarchical site structures (category → entity → details).
• Ability to handle changing site structures and implement resilient scraping strategies (selectors, fallbacks, retries).
• Ability to clean, normalize, and validate scraped data; deliver in CSV, JSON, or Google Sheets.
• Experience with batching/parallelization or equivalent approaches for scaling scraping jobs.
• Familiarity using LLMs/AI tools to accelerate workflows (prompting, automation, extraction assistance).
• English level B2+ (upper-intermediate or higher) with ability to follow detailed specs and document edge cases clearly.
Who should apply
Apply if you enjoy solving brittle scraping problems, producing production-ready datasets, and combining coding with thoughtful QA. This is a good fit for engineers, data wranglers, and automation specialists who want flexible, remote work contributing to AI training.
• Intermediate-level contributors (1+ year) who want steady, part-time contract work (20+ hrs/week).
• People comfortable working independently and documenting technical decisions and edge cases.
• Contributors who can balance automation with human review to ensure high-quality outputs for fine-tuning and evaluation.
How the contract works
This is a contractor, part-time role paid hourly through OpenTrain AI at $20 USD/hour. You will be asked to follow detailed specs, submit validated outputs, and document your process and edge cases.
We evaluate candidates on technical skill, problem-solving, ability to follow specs, and clear documentation. Successful contributors may receive repeat work on similar scraping and data-prep projects.
• Schedule: Flexible, remote, 20+ hours/week.
• Payment: Pay-per-hour at $20 USD/hour.
• Work includes production of structured outputs (CSV/JSON/Sheets) and participation in AI-assisted workflows.
OpenTrain AI is the #1 platform for finding and building careers in AI training and data labeling. We connect skilled contributors with technical annotation and data-prep work that directly shapes how modern AI systems behave.
We hire and contract contributors directly. This role is an OpenTrain AI position, offered as a flexible, remote contract so you can build a technical portfolio while working around your schedule.
Why AI training and data labeling matter
AI training (also called data labeling or human feedback work) is the human side of building artificial intelligence: people prepare, review, and validate the examples models learn from. This work is highly accessible, often remote and flexible, and places contributors on the cutting edge of the field.
As a Vibecode Specialist you’ll work in a hybrid AI+human setup where AI agents automate repetitive steps and you provide quality control, troubleshooting, and critical thinking to produce high-quality training data for fine-tuning and evaluation tasks.
The role
You will own end-to-end web scraping and data-extraction workflows to produce clean, validated structured datasets from complex websites. Tasks combine hands-on coding, practical data engineering, and quality review.
Work is remote and global. Expect approximately 20+ hours per week in a contract, part-time arrangement paid at $20 USD per hour.
• Data type: Text (unlabeled source content; you will extract and normalize fields).
• Labeling focus includes coding/programming work, fine-tuning data preparation, and evaluation/rating of extracted outputs.
• You will use internal tools and your own scripts (examples: Apify, OpenRouter, Playwright/Selenium, custom Python).
What you'll do day-to-day
Deliver robust scraping workflows, validate outputs, and hand off clean CSV/JSON/Google Sheets. Troubleshoot failures and adapt when site structures change.
• Design and implement Python-based scrapers for dynamic, JavaScript-rendered sites (BeautifulSoup + Selenium/Playwright or equivalents).
• Extract multi-level site content (category → entity → details) and normalize fields to specification.
• Implement resilient scraping strategies: selector fallbacks, retries, rate controls, and error handling.
• Scale work via batching, parallelization, or other performance approaches to handle large jobs.
• Use LLMs/AI tools to accelerate extraction, prompting, or data-cleaning steps and evaluate their outputs.
• Document edge cases, follow detailed specs, and produce reproducible deliverables (CSV/JSON/Sheets).
Requirements
You must meet every stated requirement below to be considered. We do not require prior labeling platform experience, but you must be technically hands-on with scraping and data pipelines.
• 1+ year experience in at least one: web scraping, data engineering, software development, automation, or data analysis.
• Strong Python web scraping skills (e.g., BeautifulSoup plus Selenium or Playwright, or equivalent toolsets).
• Proven experience scraping dynamic/JS-heavy sites (infinite scroll, AJAX, JS-rendered content).
• Experience extracting from multi-level/hierarchical site structures (category → entity → details).
• Ability to handle changing site structures and implement resilient scraping strategies (selectors, fallbacks, retries).
• Ability to clean, normalize, and validate scraped data; deliver in CSV, JSON, or Google Sheets.
• Experience with batching/parallelization or equivalent approaches for scaling scraping jobs.
• Familiarity using LLMs/AI tools to accelerate workflows (prompting, automation, extraction assistance).
• English level B2+ (upper-intermediate or higher) with ability to follow detailed specs and document edge cases clearly.
Who should apply
Apply if you enjoy solving brittle scraping problems, producing production-ready datasets, and combining coding with thoughtful QA. This is a good fit for engineers, data wranglers, and automation specialists who want flexible, remote work contributing to AI training.
• Intermediate-level contributors (1+ year) who want steady, part-time contract work (20+ hrs/week).
• People comfortable working independently and documenting technical decisions and edge cases.
• Contributors who can balance automation with human review to ensure high-quality outputs for fine-tuning and evaluation.
How the contract works
This is a contractor, part-time role paid hourly through OpenTrain AI at $20 USD/hour. You will be asked to follow detailed specs, submit validated outputs, and document your process and edge cases.
We evaluate candidates on technical skill, problem-solving, ability to follow specs, and clear documentation. Successful contributors may receive repeat work on similar scraping and data-prep projects.
• Schedule: Flexible, remote, 20+ hours/week.
• Payment: Pay-per-hour at $20 USD/hour.
• Work includes production of structured outputs (CSV/JSON/Sheets) and participation in AI-assisted workflows.
