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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # data-driven research engineer - **Company:** PIKA, LLC - **Location:** Palo Alto, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Microsoft Azure, Big Data, Computer Programming, Data Deduplication, Information Engineering, Data Files, Data Infrastructure, Extract Transform Load (ETL), Digital Technology, Distributed Data Store, Apache Hadoop, Python (Programming Language), Machine Learning, Cloud Services, SQL Databases, Data Processing, Google Cloud, Data Ingestion, Large Language Models, Apache Spark, Pyspark, Data Management, Machine Learning Operations, Data Pipelines - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/research-scientist-data-pika-8665199 ## About the Role * 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 ## Description 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 ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Introduction to TXT](https://www.wearedevelopers.com/videos/30-introduction-to-txt) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Implementing continuous delivery in a data processing pipeline](https://www.wearedevelopers.com/videos/73-implementing-continuous-delivery-in-a-data-processing-pipeline) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)