Remote ML Data Engineer Petabyte-Scale AI Pipelines

United States Digital Space LLC; United States; Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking an ML Data Engineer to build and operate large-scale data systems powering AI training pipelines. You will own ingestion, transformation, quality assurance, lineage, and high-throughput delivery of data to training jobs across modalities.

The ideal candidate has 6+ years of data engineering experience, strong Python and JVM-language skills, and hands-on work with Spark, Ray, or Beam, plus experience operating petabyte-scale storage and data pipelines.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or a related field.
• Six or more years of data engineering experience, with ML/AI workloads.
• Strong proficiency in Python and at least one JVM language.
• Experience with Spark, Ray, or Beam.
• Hands-on experience operating petabyte-scale storage and pipelines.
• 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.

Skills

Six or more years of data engineering

Python

Java

Spark

Ray

Beam

Petabyte-scale storage

Distributed systems

Data modeling

Data versioning

CI/CD

Testing

Code review

Communication

Education

Bachelor’s or Master’s in Computer Science

Tools

N/A

Job description

Bright Vision Technologies is seeking an ML Data Engineer to build and operate large-scale data systems powering AI training pipelines. You will own ingestion, transformation, quality assurance, lineage, and high-throughput delivery of data to training jobs across modalities.

The ideal candidate has 6+ years of data engineering experience, strong Python and JVM-language skills, and hands-on work with Spark, Ray, or Beam, plus experience operating petabyte-scale storage and data pipelines.