Software Engineer, ML Data Systems

About this role

Build and maintain the data infrastructure that powers Cursor's ML-driven code automation product. You'll own the full lifecycle of data pipelines—from fixing immediate bottlenecks to redesigning systems at scale—while ensuring correctness, cost-efficiency, and privacy guarantees.

What you'll do

• Design and ship data pipeline replacements while maintaining system reliability during transitions
• Define instrumentation requirements for new product surfaces and integrate telemetry end-to-end
• Debug performance issues across client, streaming, storage, and compute layers
• Establish data contracts and schema evolution strategies to prevent silent failures across consumers
• Optimize storage costs through retention policies, compression, and strategic data deletion
• Identify and close instrumentation gaps that impact model evaluation and experimentation

What they're looking for

• Apache Spark (Databricks or open-source)
• Large-scale data pipeline design and ownership
• Data modeling and schema design
• Production debugging across infrastructure layers
• Ray Data
• ClickHouse (preferred)
• Orchestration tools (dbt, Dagster)
• Privacy-aware data systems

Benefits

• In-person offices in North Beach (San Francisco) and Manhattan (New York)
• Flat organizational structure with small, talented team
• Ownership of high-impact systems that directly enable product teams
• Daily shipping culture with focus on quality and correctness