Research Scientist, Data

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

Benefits offered by this job

Competitive salary

Equity

Health benefits

401k matching

Flexible hybrid work

Job summary

Pika is hiring a staff or lead Research Engineer, Data to architect and scale data pipelines for multimodal foundation models. You will collaborate with research and engineering to curate diverse datasets and build robust ML data infrastructure.

Responsibilities include end-to-end data ingestion, labeling tools, and privacy considerations, with a strong emphasis on production-ready systems. This remote-friendly role supports US-based applicants from a company focused on real-time multimodal

Qualifications

• 5+ years of experience building and scaling data pipelines for ML applications at staff or lead level.
• Strong background in data engineering and ML data curation for LLMs/VLMs.
• Expertise in distributed data systems (e.g., Spark, Hadoop, Ray).
• Proven ability to build robust, scalable data infrastructure for ML pipelines.
• Experience developing tools for data labeling, filtering, deduplication, QA, and dataset management.
• Strong programming skills (Python, SQL, PySpark).
• Knowledge of privacy, compliance, ethics in data collection and management.
• Excellent cross-functional collaboration and communication skills.
• Passion for enabling cutting-edge generative AI through data excellence.

Responsibilities

• Take ownership of large-scale data pipeline architecture and implementation supporting model training and research workflows for multimodal datasets.
• Partner with research and engineering teams to curate and manage diverse datasets for pre-training and mid-training.
• Develop strategies and tools for scalable data ingestion, labeling, filtering, augmentation, and storage.
• Ensure data quality, reliability, and privacy/compliance across the data lifecycle.
• Optimize data processing and delivery for large-scale distributed training pipelines.
• Prototype and productionize new methods for dataset creation and management.
• Integrate research-driven data advancements into production-ready systems.
• Stay updated on emerging data engineering and ML data management developments.

Skills

Data pipelines for ML

ML data curation

Distributed data systems

Data infrastructure

Data labeling tools

Python/SQL/PySpark

Data privacy/ethics

Collaboration

Generative AI data

Tools

Spark

Hadoop

Ray

PySpark

AWS

GCP

Azure

Python

SQL

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!

If you are a data-driven research engineer excited to lead and scale the data infrastructure powering real-time multimodal foundation models, we want to hear from you.

This is a remote role. Applicants must be located in: United States.