Remote ML Data Engineer — Large-Scale Pipelines

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

Benefits offered by this job

Remote work

Career growth

Job summary

Bright Vision Technologies is seeking a Machine Learning Data Engineer to design and operate large-scale data systems powering AI training pipelines. The role emphasizes ingestion, transformation, quality assurance, lineage and high-throughput data delivery across modalities.

The ideal candidate has 6+ years of data engineering, strong Python, and experience with Spark, Ray, or Beam, plus petabyte-scale storage and robust software practices.

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.
• Ensure ingestion, transformation, quality assurance, lineage and high-throughput delivery of data to training jobs.
• Apply practical software engineering principles to data infrastructure to improve model quality and training efficiency.

Skills

Python

Java

Distributed systems

Data pipelines

Education

Bachelor's or Master's in CS

Tools

Spark

Ray

Beam

CI/CD

Job description

Bright Vision Technologies is seeking a Machine Learning Data Engineer to design and operate large-scale data systems powering AI training pipelines. The role emphasizes ingestion, transformation, quality assurance, lineage and high-throughput data delivery across modalities.

The ideal candidate has 6+ years of data engineering, strong Python, and experience with Spark, Ray, or Beam, plus petabyte-scale storage and robust software practices.