Research Scientist, Data

About the Role

At Pika, we are pioneering the next generation of creative infrastructure built around real-time, multimodal generation and intelligent agentic platforms. We are looking for a staff or lead-level Research Engineer, Data to architect and scale data engineering systems supporting model training for our advanced multimodal foundation models. This pivotal role will strengthen our research teams by building, optimizing, and owning large-scale data pipelines and robust ML data curation, ensuring our foundation models have access to the highest quality and most diverse datasets. If you are passionate about powerful data infrastructure and innovative research-engineering, join us to make an impact for millions of creators.

What You’ll Do

Take ownership of large-scale data pipeline architecture and implementation to support model training and research workflows for text, image, audio, and video datasets

Partner with research and engineering teams to curate, clean, and manage diverse, sensory-rich datasets for pre-training and mid-training of multimodal models

Develop strategies and tools for scalable data ingestion, labeling, filtering, augmentation, and storage

Ensure data quality, reliability, and compliance, including managing privacy and ethical considerations throughout the data lifecycle

Optimize data processing, transformation, and delivery for large-scale distributed training pipelines

Prototype and productionize new methods for dataset creation, management, and continuous improvement in response to researcher needs

Contribute to the integration of research-driven data advancements into production-ready systems

Stay informed on emerging data engineering and ML data management developments, bringing best practices to our systems

What We’re Looking For

5+ years of experience building and scaling data pipelines for machine learning applications at staff or lead engineer level, ideally in research or model training environments

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) and efficient large dataset processing/ETL workflows

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) and 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

Passion for enabling cutting-edge generative AI and creative technology through data excellence

What We Offer

Competitive salary and substantial equity in a high-growth startup

Full health benefits, 401k matching, and more