Data Engineer (ML Platform & Data Foundations)

Intuitive•San Francisco, CA

About The Position

We are looking for a Data Engineer to build and own the data foundations that power machine learning and analytics, with a strong focus on image or and video data. This role is focused on designing pipelines to ingest, process, and organize large-scale visual datasets for machine learning applications. You will work closely with ML scientists, data scientists, and software engineers to ensure data is reliable, discoverable, and production ready.

Requirements

3+ years of experience as a Data Engineer or in a similar role, primarily working with image or video data
Strong proficiency in Python
Experience with cloud data platforms (AWS or GCP)
Experience in Docker and Linux

Nice To Haves

Advanced degree or relevant certifications are a plus, but not required

Responsibilities

Build and maintain data pipelines for image and video datasets used by ML models
Handle visual data ingestion, processing, validation and storage across system
Extract and organize large media files and related metadata
Optimize data systems for performance and reliability including handling large binary data
Debug and fix issues in data pipelines and datasets
Organize datasets so they can be reliably used for model training and evaluation
Define and maintain schemas, metadata, and data documentation
Implement data quality checks, validation frameworks, and monitoring
Support data versioning, lineage, and reproducibility across evolving datasets
Partner closely with ML scientists to understand data requirements
Prepare and maintain datasets used for training and testing models
Support ML workflows by ensuring consistent, high-quality data inputs
Enable smooth handoff from experimentation to production
Collaborate with product, analytics, and engineering teams to align data solutions with business needs
Establish best practices for data modeling, pipeline design, and governance
Contribute to architectural decisions for data and ML platforms