Research Scientist, Data

pika; United States; Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive salary & equity

Full health benefits

Hybrid on-site/remote (HQ Palo Alto)

Job summary

Pika is seeking a staff or lead-level Research Engineer, Data to architect and scale data pipelines for multimodal foundation models. You will own data ingestion, labeling, quality, and privacy, enabling high-quality training datasets across text, image, audio, and video.

Join a collaborative, fast-growing startup with HQ in Palo Alto, offering full benefits and equity, hybrid work, and opportunities to influence cutting-edge generative AI research.

Qualifications

• 5+ years building and scaling data pipelines for ML in staff/lead roles.
• Experience with LLMs, VLMs, or multimodal model data curation.
• Proficient in distributed data systems (Spark, Hadoop, Ray).
• Proven ability to deploy production-grade ML data infrastructure.
• Strong Python/SQL and cloud platform skills (AWS, GCP, Azure).
• Knowledge of data privacy, ethics, and governance.

Responsibilities

• Own large-scale data pipeline architecture to support model training.
• Curate and manage diverse multimodal datasets.
• Develop scalable data ingestion, labeling, filtering, augmentation, storage.
• Ensure data quality, privacy, and compliance.
• Optimize data processing for distributed training pipelines.
• Prototype data management tools aligned with researcher needs.
• Integrate data innovations into production-ready systems.
• Stay updated on ML data management best practices.

Skills

Data pipelines

ML data curation

Distributed data systems

Python

SQL

Cross-functional collaboration

Problem solving

Tools

Spark

Hadoop

Ray

PySpark

AWS

GCP

Azure

Job description

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

• Collaborative, mission-driven team environment with major growth opportunities

• Flexible on-site/remote hybrid (HQ in Palo Alto, CA)

About Pika

Pika empowers creators by building state-of-the-art agentic and multimedia platforms. Our vision is to break down technical barriers to creativity, making real-time generative and intelligent orchestration accessible to all. Join us and help shape the next evolution of creative technology!