Build and own high-scale sensor data pipelines that ingest, process, QC, and deliver multi-modal physical-world data (video, depth, inertial, audio) to train frontier robotics and physical AI models. Requires strong production data engineering experience with video/sensor data at petabyte scale.
Own end-to-end multi-million-dollar code data programs for frontier AI labs. Decompose model weaknesses, design human/synthetic/hybrid data pipelines, manage expert teams, and serve as the trusted technical partner to researchers. Requires strong coding literacy, ML familiarity, and operational ownership to deliver high-quality data under tight timelines.
Builds scalable financial data infrastructure and AI-powered automation for finance operations, integrating tools like dbt, Snowflake, and agentic workflows to replace manual processes. Requires 3+ years in finance ops/data engineering, SQL/Python proficiency, and finance domain expertise.
Builds and maintains scalable data pipelines for ingestion, transformation, and reliability using SQL, Python, dbt, and Fivetran to support data science, engineering, and product teams. Requires proven data engineering experience with modern data stack tools.
Build and own high-scale sensor data pipelines that ingest, process, QC, and deliver multi-modal physical-world data (video, depth, inertial, audio) to train frontier robotics and physical AI models. Requires strong production data engineering experience with video/sensor data at petabyte scale.
Own end-to-end multi-million-dollar code data programs for frontier AI labs. Decompose model weaknesses, design human/synthetic/hybrid data pipelines, manage expert teams, and serve as the trusted technical partner to researchers. Requires strong coding literacy, ML familiarity, and operational ownership to deliver high-quality data under tight timelines.
Builds scalable financial data infrastructure and AI-powered automation for finance operations, integrating tools like dbt, Snowflake, and agentic workflows to replace manual processes. Requires 3+ years in finance ops/data engineering, SQL/Python proficiency, and finance domain expertise.
Builds and maintains scalable data pipelines for ingestion, transformation, and reliability using SQL, Python, dbt, and Fivetran to support data science, engineering, and product teams. Requires proven data engineering experience with modern data stack tools.