Member of Technical Staff — ML Data Infra

What You'll Do

• Design, build, and operate large-scale data pipelines for ingestion, processing, filtering, and curation of multimodal training data (video, audio, text)
• Take research-grade data processing code and turn it into robust, production-level pipelines — quickly and without losing correctness
• Optimize pipeline throughput and efficiency at scale; identify and eliminate bottlenecks across compute, I/O, and storage
• Build and maintain data quality systems — deduplication, filtering, validation, and quality scoring at scale
• Manage petabyte-scale datasets: storage architecture, versioning, lineage tracking, and cost efficiency
• Work closely with researchers to understand data requirements and translate them into scalable processing systems
• Build tooling and infrastructure that makes the research team faster — efficient data access, reproducible processing, and fast iteration loops

What We're Looking For

• Proven experience building and operating large-scale data pipelines in production — you've processed data at a scale where naive approaches break
• Strong proficiency with distributed data processing frameworks — Spark, Ray, Dask, or similar — and a clear sense of when to use each
• Solid software engineering fundamentals: you write clean, testable, maintainable code and understand why that matters when pipelines run unattended at scale
• Experience with multimodal data (video, audio) is a strong plus — understanding of formats, codecs, and processing libraries (FFmpeg, decord, etc.)
• Familiarity with ML data pipelines specifically — understanding of how data quality and format affect model training
• Ability to move fast: you can take a prototype script from a researcher and ship a production version in days, not weeks

Bonus Points

• Experience building data pipelines for large-scale model training (pre-training or fine-tuning)
• Familiarity with data versioning and lineage tools (DVC, Delta Lake, Apache Iceberg, etc.)
• Experience with streaming data pipelines or online data processing
• Prior work at an AI lab, video platform, or other data-intensive company
• Contributions to open-source data tooling

Compensation

• $200,000 – $300,000 base salary, plus meaningful equity
• Health: HSA plan with ~$2,000 in company contributions
• PTO: 15 days + public holidays, and we close for a full week over the holidays
• Lunch, beverages, and snacks on us every workday
• Commuter benefits
• 401K: In the works