Machine Learning Engineer - Data Scrapping
Data Science at TRACTIAN
The Data Science team at TRACTIAN focuses on extracting valuable insights from vast amounts of industrial data. Using advanced statistical methods, algorithms, and data visualization techniques, this team transforms raw data into actionable intelligence that drives decision-making across engineering, product development, and operational strategies. The team constantly works on optimizing prediction models, identifying trends, and providing data-driven solutions that directly enhance the company’s operational efficiency and the quality of its products.
What you'll do
We’re looking for software and data engineers to join our newly established Data Gathering and Labeling (DGL) team. In this role, you'll be critical to building Tractian's comprehensive and diverse datasets, from industrial equipment documentation to sensor data like vibration and temperature. Your work will directly power new features in our platform and enhance our competitive advantage through richer and more reliable data resources.
Responsibilities
- Design and maintain robust data collection pipelines from a wide range of sources, including websites, documents, APIs, and raw sensor data
- Extract and structure information from unstructured or semi-structured formats into clean, standardized schemas
- Handle real-world data challenges like pagination, rate limits, CAPTCHAs, noise, missing values, and inconsistent formatting
- Clean, filter, and validate raw data to ensure high quality, consistency, and usability across our systems
- Develop small tools and utilities to support and automate data collection workflows
- Support the creation and maintenance of labeling pipelines for ML applications
- Collaborate with engineering and product teams to optimize data storage and access patterns
- Document data sources, collection methodologies, and processing procedures for reproducibility
Requirements
- 0–2 years of experience in software development, data engineering, or related fields
- Degree in Computer Science, Computer Engineering, Information Systems, or equivalent technical background
- Understanding of HTML, CSS selectors, and how web pages are structured
- Strong problem-solving skills and an eye for detail
- Ability to work in a fast-paced environment and manage shifting priorities
Technical Skills
- Proficiency in Python, especially for data manipulation and automation
- Experience (academic or professional) with data extraction using tools like `requests`, `BeautifulSoup`, or similar
- Familiarity with REST APIs and the HTTP protocol
- Experience with data cleaning techniques such as:
- Handling missing or inconsistent values
- Removing duplicates and outliers
- Standardizing formats (e.g., dates, units, text normalization)
- Validating data against schemas or expected ranges
- (Optional) Exposure to browser automation tools like Selenium or Playwright
Nice to Have
- Experience with web scraping libraries/frameworks like Scrapy, Playwright, or Selenium
- Familiarity with proxy usage, headless browsers, or CAPTCHA bypass techniques
- Understanding of database systems (SQL or NoSQL)
- Exposure to rapid prototyping tools like Streamlit
- Previous experience working with or around industrial equipment or maintenance systems
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