Build and operate core data systems and pipelines for AI research and production. Design scalable ingestion, processing, and orchestration for batch and streaming workloads. Requires strong data engineering background, experience with large-scale data systems, and a bias for action.
Key Highlights
Build foundational data infrastructure for AI model development.
Design and implement scalable batch and streaming data pipelines.
Drive data quality, governance, and cost/performance management.
Key Responsibilities
Build and operate company-wide foundations platform.
Build and operate core data systems and pipelines.
Design ingestion and orchestration patterns for batch and streaming workloads.
Build scalable compute and storage foundations.
Ensure reproducible pipelines through versioning, backfills, and isolated execution environments.
Provide trusted data quality, lineage, and governance signals.
Maintain predictable cost and performance through guardrails, budgets, and continuous system tuning.
Enable a unified data layer that supports research, training, and production.
Technical Skills Required
Data Engineering
Batch Processing
Streaming Processing
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Benefits & Perks
Top-tier compensation
Stock options
Health & wellness
Paid parental leave
Unlimited paid time off (US)
30 days paid time off (UK)
Visa sponsorship support
Nice to Have
Spark
Flink
Beam
Airflow
Dagster
Kafka
PubSub
Parquet
Iceberg
Delta Lake
BigQuery
Snowflake
Great Expectations
Job Description
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.FoundationsBuild 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.
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