Remote ML Data Engineer | Petabyte-Scale Pipelines

Bright Vision Technologies; Artesia, Cerritos (CA, CA); Remote; USD 80,000 - 100,000; Full time

Job summary

Bright Vision Technologies is seeking a Machine Learning Data Engineer to build and operate large-scale data systems that power modern AI training pipelines. This role emphasizes data ingestion, transformation, quality checks, lineage, and high-throughput delivery of data for diverse AI workloads.

The ideal candidate will have 6+ years of data engineering experience, strong Python skills, and experience with Spark, Ray, or Beam.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or a related field.
• 6+ years of data engineering experience, with ML/AI workloads.
• Strong Python and at least one JVM or systems language.
• Deep experience with 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.

Responsibilities

• Build and operate large-scale data systems powering AI training pipelines.
• Oversee ingestion, transformation, quality assurance, lineage, and high-throughput data delivery to training jobs.
• Contribute to data infrastructure decisions impacting model quality and training efficiency.
• Maintain reliability and performance of data pipelines across modalities.

Skills

Python

CI/CD

Code review

Distributed systems

Data modeling

Communication

ML pipelines

Education

Bachelor’s or Master’s degree in Computer Science or related field

Tools

Spark

Ray

Beam

Big data storage

Job description

Bright Vision Technologies is seeking a Machine Learning Data Engineer to build and operate large-scale data systems that power modern AI training pipelines. This role emphasizes data ingestion, transformation, quality checks, lineage, and high-throughput delivery of data for diverse AI workloads.

The ideal candidate will have 6+ years of data engineering experience, strong Python skills, and experience with Spark, Ray, or Beam.