The opportunity
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
What you'll do
Design, build, and operate scalable batch and appropriate streaming data pipelines.
Own ETL/ELT architecture, orchestration, warehouse models, and reusable data-engineering frameworks.
Lead data migrations, schema evolution, backfills, retention, archival, and recovery.
Handle late, duplicate, missing, and changing data through contracts, idempotency, validation, and replay.
Define data-quality checks, lineage, monitoring, alerting, SLAs/SLOs, and incident-response practices.
Improve platform performance, reliability, scalability, and cost efficiency.
What they're looking for
- Partner with analytics, software, infrastructure, and business stakeholders: to translate requirements into durable data products.
- Review designs and code, mentor engineers, and raise standards for testing,: documentation, deployment, and operations.
- Make and communicate long-term architecture tradeoffs across teams.
- Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience.
