Remote ML Data Engineer — Petabyte-Scale 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. The role focuses on ingestion, transformation, quality, lineage, and high-throughput data delivery for diverse modalities.

The ideal candidate has 6+ years of data engineering experience, strong Python skills, and experience with Spark, Ray, or Beam, plus knowledge of petabyte-scale storage and distributed systems.

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.

Responsibilities

• Build and operate large-scale data systems powering AI training and evaluation pipelines.
• Focus on ingestion, transformation, quality, lineage, and high-throughput delivery of data to training jobs.
• Ensure data infrastructure choices support model quality and training efficiency.

Skills

Python

Distributed systems

Data engineering

CI/CD

Communication

Education

Bachelor’s or Master’s degree 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. The role focuses on ingestion, transformation, quality, lineage, and high-throughput data delivery for diverse modalities.

The ideal candidate has 6+ years of data engineering experience, strong Python skills, and experience with Spark, Ray, or Beam, plus knowledge of petabyte-scale storage and distributed systems.