Remote ML Data Engineer for Large-Scale AI Pipelines

Bright-Vision-Technologies; United States; Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking an ML Data Engineer to design and operate large-scale data systems powering AI training and evaluation pipelines. This fully remote role focuses on 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, expertise in Python and a JVM language, and hands-on experience with Spark, Ray, or Beam, plus petabyte-scale storage and

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 or systems language.
• Deep experience with Spark, Ray, or Beam.
• Hands-on experience operating petabyte-scale storage and pipelines.
• 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.

Responsibilities

• Build and operate large-scale data systems powering AI training and evaluation pipelines.
• Focus on ingestion, transformation, quality assurance, lineage, and delivery of data to training jobs.
• Collaborate across teams to ensure data quality and model training efficiency.

Skills

Python

Java

Distributed systems

Data modeling

Data lineage

CI/CD

Testing

Cross-functional collaboration

Education

Bachelor's or Master's in Computer Science or related field

Tools

Spark

Ray

Beam

Job description

Bright Vision Technologies is seeking an ML Data Engineer to design and operate large-scale data systems powering AI training and evaluation pipelines. This fully remote role focuses on 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, expertise in Python and a JVM language, and hands-on experience with Spark, Ray, or Beam, plus petabyte-scale storage and