Member of Technical Staff, Data & ML Infrastructure for Video Models

About the Role:

We are looking for a new Member of Technical Staff to build and scale the data pipelines behind our large video generation models. This role is focused on collecting large amounts of relevant video data, preparing high-quality training samples, and developing robust preprocessing, filtering, and parsing workflows. You'll orchestrate annotation pipelines across platforms such as MTurk and own the full lifecycle of training data, from raw ingestion to clean, model-ready samples that directly drive quality improvements. This role sits at the intersection of data engineering and ML research, making it central to how we turn messy real-world data into the fuel that moves our models forward.

What You’ll Do:

• Build and maintain data pipelines for large video generation models, including data ingestion, parsing, filtering, preprocessing, and dataset curation at scale, using tools such as AWS S3 and DynamoDB.

• Design and run annotation workflows across platforms such as MTurk, Prolific, and Mechanical Turk, including task design, quality control, and label validation.

• Train, evaluate, and improve smaller supporting models used for data filtering, quality assessment, preprocessing, or other parts of the ML pipeline.

• Partner closely with research and engineering teams to turn experimental workflows into scalable, repeatable systems that support model training and evaluation.