Member of Technical Staff - Data Ingestion Engineer

Department: Engineering

Location: San Francisco, New York, London

Employment Type: FullTime

Our Mission

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

We’re developing open weight models for individuals, agents, enterprises, and even nation states. Our team of AI researchers and company builders come from DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic and beyond.

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 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 define the frontier 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 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 you need it, relocation support, and more perks that optimize your time.

• Opportunities to connect with teammates: lunch and dinner are provided daily. We have regular off-sites and team celebrations.