Member of Technical Staff - Data Ingestion Engineer

Sierra Ventures; San Francisco (CA); Hybrid; USD 180,000 - 280,000; Full time

Benefits offered by this job

Top-tier compensation

Stock options

Health & wellness coverage

Meals in office

Parental leave (22 weeks)

Unlimited vacation (US)

Visa sponsorship

Job summary

Reflection is seeking a data engineer to build and operate ingestion systems for pre‑training at scale. You will own web crawling, extraction, normalization, and delivery pipelines, working with researchers to align data with model goals.

You will run experiments, analyze data quality, and ensure observability and reliability across multi‑TB to PB datasets in a hybrid research‑engineering team.

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

Responsibilities

• Build and operate ingestion systems for pre‑training at large scale
• Run experiments to evaluate crawling strategies and ingestion tradeoffs
• Analyze ingested data to identify gaps and redundancies
• Build scalable ingestion pipelines for large data campaigns
• Review code and debug production issues, improving ingestion infrastructure

Skills

Web crawling

Data ingestion

LLM knowledge

Experiment design

Communication skills

Tools

Ray

Beam

Spark

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