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.

Foundations

Vision:

Build and operate a company-wide foundations platform that accelerates every team by providing reliable, scalable developer infrastructure, SRE capabilities, and high-throughput data ingestion tooling enabling Reflection to move faster as we scale.

What This Team Does

Build and operate the core data systems and pipelines that power our research, training, and production environments. This platform enables high-velocity experimentation, reliable model development, and scalable production workflows by unifying ingestion, processing, and orchestration across the data lifecycle.

• Design ingestion and orchestration patterns for both batch and streaming workloads.

• Build scalable compute and storage foundations (formats, engines, runtimes) that support large-scale data processing.

• Ensure reproducible pipelines through versioning, backfills, and isolated execution environments.

• Provide trusted data quality, lineage, and governance signals so teams can make confident production decisions.

• Maintain predictable cost and performance through guardrails, budgets, and continuous system tuning.

• Enable a unified data layer that supports research, training, and production across the model development lifecycle.

About the Role

Build the core data systems and pipelines that power our research, training, and production environments. Design and implement reliable, scalable ingestion and orchestration patterns for batch and streaming workloads. Develop the storage and compute foundations that enable reproducible experimentation and high-velocity iteration. Drive data quality and governance standards that teams can trust for production decisions. Provide the foundational data layer that unifies ingestion, processing, and workflow management across model development.

What You'll Work With

• Compute & Orchestration: Spark, Flink, Beam, Airflow, Dagster, Kafka, PubSub.

• Storage & Analytics: Data lake and warehouse architectures, Parquet, Iceberg, Delta Lake, BigQuery, Snowflake.

• Metadata & Data Quality: Lineage systems, metadata management, Great Expectations, reproducibility systems.