Member of Technical Staff, Data Ingestion Engineer

The role

You will build and operate ingestion systems that turn the open web and large-scale data sources into structured corpora for training frontier models. You will work with researchers to acquire, extract, normalize, version, and deliver data to pre-training pipelines.

What you will do

• Build and operate large-scale data ingestion systems for pre-training
• Run experiments to evaluate crawling strategies, extraction methods, and ingestion tradeoffs
• Analyze ingested data to identify gaps, redundancy, and areas to improve
• Build ingestion pipelines that scale reliably across large data campaigns
• Develop specialized crawlers for high-priority data sources
• Review code, debug production issues, and continuously improve ingestion infrastructure

Required qualifications

• Experience building web crawling, data ingestion, or large-scale data acquisition systems using Ray, Beam, Spark, or similar technologies
• Familiarity with how LLMs are trained and evaluated
• Intuition for what makes data useful for training
• Comfortable working with very large datasets (multi-TB to PB scale)
• Ability to build systems that are observable, testable, and maintainable
• Comfortable designing experiments and using data to guide system improvements
• Excellent communication skills

Benefits

• Salary and equity
• Stock options
• Comprehensive medical, dental, vision, and life
• Annual wellness allowance
• Lunch and dinner provided in the office daily
• 22 weeks paid parental leave for all new birthing and non-birthing parents, including adoptive and surrogate journeys
• Unlimited paid time off in the U.S.
• 30 days paid time off in the U.K.
• Visa sponsorship support
• Regular off-sites, happy hours, and team celebrations

Before you apply

• Position may require access to technology or source code subject to U.S. Export Administration Regulations
• Offer may be conditioned on the ability to provide access in compliance with U.S. export control laws

About the company

Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on. They build open models to help shape the future of AI.