Reflection ai

Reflection ai

Reflection is a research lab dedicated to making intelligence open and accessible for everyone. We build open models that empower individuals to control their intelligence and shape the future of AI. This role focuses on the foundational aspects of AI development, specifically in pre-training data, contributing to the creation of open foundational models. You will be part of a talented team, helping to define the company's future and the future of open AI.

Reflection ai

Reflection's Data team is responsible for building the training corpora that our frontier models learn from. The ingestion layer is the critical machinery that transforms raw data from the open web, licensed sources, and other large-scale origins into well-structured, versioned, and auditable datasets for pre-training. As the Data Ingestion Lead, you will provide front-line leadership for the team responsible for this layer, overseeing web crawl, data ingestion pipelines, and data lakes. You will build, mentor, and grow a team of data ingestion engineers, guide technical and architectural decisions across crawling, extraction, and corpus storage/delivery, and collaborate closely with research, data quality, and data partnerships teams. You will also remain hands-on to contribute technically and maintain a deep understanding of the team's work, as subtle decisions at the ingestion layer significantly impact model performance, safety, and failure points.

Reflection ai

Reflection is a research lab dedicated to making intelligence open and accessible. We build open models that empower users to control their intelligence and shape the future of AI. In this role, you will develop the critical evaluation infrastructure that researchers rely on to understand model capabilities, inform training decisions, and assess readiness for release. Your work will encompass evaluation authoring, distributed execution, and results analysis, with a specific emphasis on pre-training. You will collaborate closely with researchers to enhance the speed, reliability, and ease of use of evaluations, ensuring that the outcomes accurately reflect the models being assessed.

Reflection ai

Reflection is a research lab dedicated to making intelligence open and accessible. We build open models that empower individuals to control their AI and shape its future. This role focuses on designing and operating large-scale multilingual data pipelines, ensuring the quality and effectiveness of data used for training advanced language models. You will contribute to scientific experiments aimed at improving multilingual data efficiency in large language models and develop evaluation sets to identify and address model performance gaps across different languages and domains.