Job description

OUR MISSION Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on. We build open models that let anyone control their intelligence and help shape the future of AI. Our mission: make intelligence open and accessible to all. ABOUT THE ROLE Data is playing an increasingly crucial role at the frontier of AI innovation. Many of the most meaningful advances in recent years have come not from new architectures, but from better data. As a member of the Data Team, your mission is to build and operate the ingestion systems that turn the open web and other large-scale data sources into reliable, well-structured corpora for training frontier models. You will own the machinery that acquires, extracts, normalizes, versions, and delivers data to our pre-training pipelines. You’ll work directly with world-class researchers to close the loop between what we collect and how it impacts model performance. This role is ideal for engineers who love building robust distributed systems, but who also want to run experiments, reason about tradeoffs in data acquisition, and iterate quickly based on measurable impact. Working closely with our pre-training and data quality teams, you will: - Build and operate large-scale data ingestion systems for pre-training, including web crawling, extraction, and dataset delivery - 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 ABOUT YOU: - Curious about how training data influences model capabilities, and can iterate quickly based on measurable downstream impact - Able to collaborate tightly across functions: researchers, infra, operations, and external partners. - Enjoy working in a hybrid research–engineering role SKILLS AND 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, and an intuition for what makes data useful for training - Comfortable working with very large datasets (multi-TB to PB scale) and building systems that are observable, testable, and maintainable - Comfortable designing experiments and using data to guide system improvements - Excellent communication skills. You can explain system behavior. You consider and communicate tradeoffs clearly WHAT WE OFFER: We believe that to make intelligence open and accessible to all, you need to start at the foundation. Joining Reflection means building from the ground up as part of a talent-dense team. You will help define our future as a company, and help define the future of open foundational models. We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported. - Top-tier compensation: Salary and equity structured to recognize and retain our talent globally. - Stock options: Everyone who joins and contributes to Reflection's success gets to share in the upside through stock options. - Health & wellness: Comprehensive medical, dental, vision, and life, with an annual wellness allowance. - Meals: Lunch and dinner are provided in the office daily. - Life & family: 22 weeks paid parental leave for all new birthing and non-birthing parents, including adoptive and surrogate journeys. - Vacation days: Unlimited paid time off in the U.S. and 30 days in the U.K. - Sponsorship support: We sponsor visas to help exceptional talent join our team and support long-term immigration pathways where applicable. - Team building: We have regular off-sites, happy hours, and team celebrations. Export Control Notice: This position may require access to technology or source code subject to the U.S. Export Administration Regulations. Any offer of employment for this role may be conditioned on the Company's ability to provide the candidate with access to such technology or source code in compliance with applicable U.S. export control laws, which may require the Company to seek government authorization. Candidate and Employee Privacy Notice: We collect and process personal data about applicants for the purposes described in our Candidate and Employee Privacy Notice cdn.sanity.io

Requirements

Must-haves

Data is playing an increasingly crucial role at the frontier of AI innovation. Many of the most meaningful advances in recent years have come not from new architectures, but from better data.
Working closely with our pre-training and data quality teams, you will:
Build and operate large-scale data ingestion systems for pre-training, including web crawling, extraction, and dataset delivery
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
Curious about how training data influences model capabilities, and can iterate quickly based on measurable downstream impact
Able to collaborate tightly across functions: researchers, infra, operations, and external partners.
Enjoy working in a hybrid research–engineering role
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, and an intuition for what makes data useful for training
Comfortable working with very large datasets (multi-TB to PB scale) and building systems that are observable, testable, and maintainable
Comfortable designing experiments and using data to guide system improvements
Excellent communication skills. You can explain system behavior. You consider and communicate tradeoffs clearly

Nice-to-haves

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Keywords to mirror

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

Paid Time Off

Parental Leave

Wellness