Remote ML Data Engineer for Scalable AI Pipelines

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

Job summary

Bright Vision Technologies in the United States is seeking an ML Data Engineer to design and operate large-scale data pipelines for AI training and evaluation. The role emphasizes ingestion, transformation, quality assurance, lineage, and high-throughput data delivery across diverse modalities to support petabyte-scale workloads and reliable model development.

You will collaborate with data scientists and software engineers, contribute to robust testing, CI/CD, and documentation, and work fully

Qualifications

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

Python

Java / JVM

Spark

Ray

Beam

Petabyte storage

Distributed systems

Data modeling

Storage formats

Dataset versioning

ML lineage

Reproducibility

High-throughput loading

Accelerator training

Testing

CI/CD

Code review

Communication

Cross-functional collaboration

Education

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

Job description

Bright Vision Technologies in the United States is seeking an ML Data Engineer to design and operate large-scale data pipelines for AI training and evaluation. The role emphasizes ingestion, transformation, quality assurance, lineage, and high-throughput data delivery across diverse modalities to support petabyte-scale workloads and reliable model development.

You will collaborate with data scientists and software engineers, contribute to robust testing, CI/CD, and documentation, and work fully