Member of Technical Staff - Data Ingestion Engineer

Reflection; New York (NY); Hybrid; USD 100,000 - 130,000; Full time

Benefits offered by this job

Top-tier compensation

Comprehensive health insurance

Fully paid parental leave

Paid time off

Daily lunch and dinner

Regular team celebrations

Job summary

Reflection, located in New York, is searching for a Data Engineer to build robust data ingestion systems essential for AI training. The ideal candidate will be skilled in web crawling and data acquisition, comfortable working with large datasets, and have excellent communication abilities. The role emphasizes collaboration with researchers and iterative processes based on measurable impact. Benefits include top-tier compensation, health insurance, paid parental leave, and opportunities for team engagement.

Qualifications

• Experience building systems using Ray, Beam, Spark, or similar.
• Familiarity with LLM training and evaluation.
• Ability to work with large datasets (multi-TB to PB).
• Excellent communication skills.

Responsibilities

• Build and operate data ingestion systems for pre-training.
• Run experiments on strategies and methods.
• Analyze ingested data for gaps and improvements.
• Develop specialized crawlers for high-priority sources.

Skills

Web crawling

Data ingestion

Large-scale data acquisition

Ray

Beam

Spark

Communication skills

Job description

Our Mission

Reflection’s mission is to build open superintelligence and make it accessible to all.

About The Role

Data plays a crucial role at the frontier of AI innovation. Many advances 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, working 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, run experiments, reason about tradeoffs, and iterate quickly based on measurable impact.

Responsibilities

• 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 for improvement.
• 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—able to explain system behavior and communicate tradeoffs clearly.

What We Offer

We believe that to build superintelligence that is truly open, you need to start at the foundation. Joining Reflection means building from the ground up as part of a small talent‑dense team. You will help define our future as a company and help shape the frontier of open foundational models.

• Top‑tier compensation: salary and equity structured to recognize and retain the best talent globally.
• Health & wellness: comprehensive medical, dental, vision, life, and disability insurance.
• Life & family: fully paid parental leave for all new parents, including adoptive and surrogate journeys; financial support for family planning.
• Benefits & balance: paid time off when needed, relocation support, and perks that optimize your time.
• Opportunities to connect with teammates: lunch and dinner are provided daily; regular off‑sites and team celebrations.