MLabs logo

Research Crawling Engineer

Job Overview

Location

New York, New York, United States

Job Type

Full-time

Category

Software Engineering

Date Posted

April 29, 2026

Full Job Description

📋 Description

  • As a Research Crawling Engineer at MLabs, you will design and operate large-scale web data acquisition systems that power advanced AI model development by delivering massive-scale public web data to research organizations.
  • Day to day, you will construct and maintain distributed web crawlers across diverse domains, build high-throughput fault-tolerant data collection systems handling millions to billions of URLs per day, navigate anti-bot measures and JavaScript-heavy sites, and develop pipelines for cleaning, deduplicating, filtering, and normalizing multimodal data for machine learning training.
  • You will join a lean, technical team at MLabs that prioritizes speed, direct execution, and high output, supporting a client that operates a global-scale distributed crawler and sophisticated data ingestion pipelines for frontier AI research labs.
  • In this role, you will deepen your expertise in distributed systems, web-scale data engineering, and adversarial crawling environments while contributing directly to the creation of high-quality datasets used in frontier AI research and model training.

Skills & Technologies

Python
JavaScript
Java
Rust
Remote
$80k-175k

Ready to Apply?

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About MLabs

MLabs is a technology company specializing in the development and implementation of advanced laboratory automation solutions. They focus on creating intelligent systems that streamline complex laboratory workflows, enhance data accuracy, and improve overall efficiency for research and development, quality control, and clinical diagnostics. Their offerings often include robotics, AI-driven software, and integrated hardware designed to automate tasks such as sample handling, analysis, and reporting. MLabs serves a diverse range of industries including pharmaceuticals, biotechnology, and healthcare, aiming to accelerate scientific discovery and improve patient outcomes through cutting-edge automation.

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