Machine Learning Data Engineer

Role Description

We are seeking a Machine Learning Data Engineer to build and operate the large-scale data systems that power modern AI training and evaluation pipelines. The role combines deep data engineering expertise with a strong understanding of AI workloads, focusing on:

• Ingestion
• Transformation
• Quality assurance
• Lineage
• High-throughput delivery of data to training jobs across diverse modalities

The ideal candidate has experience operating petabyte-scale data systems, strong software engineering fundamentals, and a clear understanding of how data infrastructure choices propagate into model quality and training efficiency.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or a related field
• Six or more years of data engineering experience, with significant work supporting ML or AI workloads
• Strong proficiency in Python and at least one JVM or systems language
• Deep experience with modern data processing frameworks such as Spark, Ray, or Beam
• Hands-on experience operating petabyte-scale storage and pipeline systems
• Strong understanding of distributed systems, data modeling, and storage formats
• Experience with dataset versioning, lineage, and reproducibility for ML workflows
• Familiarity with high-throughput data loading for accelerator-based training
• Strong software engineering practices including testing, CI/CD, and code review
• Excellent communication and cross-functional collaboration skills

Requirements

• Experience with multimodal datasets at large scale
• Familiarity with data quality tooling and dataset evaluation methodology
• Exposure to privacy-preserving data systems and regulated data handling
• Open-source contributions to data infrastructure projects
• Experience supporting frontier model training pipelines

Benefits

• 100% Remote (U.S.)
• Full-time, Direct W2
• Salary Range: $80,000–$100,000 Annually