Description:

Collaborate with model researchers and data engineers to ensure high-quality data production at petabyte scale.
Build processing pipelines and run compute to support model training with optimal data.

Requirements:

Strong fundamentals in ML and deep learning with experience in large-scale data systems.
Ability to transition between research and production engineering, conducting analyses and deploying systems.
Experience in data compositions, quality, and dataset releases.
Skills in designing and executing unbiased experiments.
Practical knowledge of distributed processing tools (e.g., Spark, Ray, Airflow).
Proficient in Python and modern model training workflows.
Strong understanding of data quality measurement and monitoring.
Ability to prioritize tasks and communicate effectively in a fast-paced environment.
Bonus: Experience with large video datasets and internal tooling for ML evaluation.

Skills