Research Scientist, Data

The role

This person will architect and scale data engineering systems to support model training for multimodal foundation models. They will build, optimize, and own large-scale data pipelines and ML data curation.

What you will do

• Take ownership of large-scale data pipeline architecture and implementation for text, image, audio, and video datasets
• Partner with research and engineering teams to curate, clean, and manage diverse datasets
• Develop strategies and tools for scalable data ingestion, labeling, filtering, augmentation, and storage
• Ensure data quality, reliability, and compliance
• Optimize data processing, transformation, and delivery for large-scale distributed training pipelines
• Prototype and productionize new methods for dataset creation and management
• Contribute to the integration of research-driven data advancements into production-ready systems
• Stay informed on emerging data engineering and ML data management developments

Required qualifications

• 5+ years of experience building and scaling data pipelines for machine learning applications at staff or lead engineer level
• Strong background in data engineering and ML data curation for LLMs, VLMs, or other large-scale multimodal models
• Expertise in distributed data systems (e.g., Spark, Hadoop, Ray, or similar)
• Proven ability to build robust, scalable, and production-grade data infrastructure for ML pipelines
• Experience developing tools for data labeling, filtering, deduplication, quality assurance, and dataset management
• Strong programming skills (Python, SQL, PySpark, or similar)
• Familiarity with cloud data platforms (AWS, GCP, Azure)
• Knowledge of privacy, compliance, ethics, and best practices in data collection and management
• Excellent cross-functional collaboration, problem-solving, and communication skills

Benefits

• Competitive salary
• Substantial equity
• Full health benefits
• 401k matching

About the company

Pika empowers creators by building state-of-the-art agentic and multimedia platforms. Their vision is to break down technical barriers to creativity.