Remote ML Data Engineer — Scale AI Data Pipelines

Bright Vision Technologies

Folsom (CA)

Remote

USD 80,000 - 100,000

Full time

3 days ago
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Job summary

Bright Vision Technologies is seeking a Machine Learning Data Engineer to build and operate large-scale data systems powering AI training and evaluation pipelines. The role blends data engineering with AI workloads, focusing on ingestion, transformation, quality assurance, lineage, and high-throughput data delivery to training jobs across modalities.

The ideal candidate has experience with petabyte-scale data systems, strong software engineering practices, and understands how data infrastructure

Qualifications

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

Skills

Python
JVM language
Distributed systems
Data engineering
CI/CD practices
Communication skills

Education

Bachelor's or Master's in Computer Science

Tools

Spark
Ray
Beam
Git
CI/CD tooling

Job description

Bright Vision Technologies is seeking a Machine Learning Data Engineer to build and operate large-scale data systems powering AI training and evaluation pipelines. The role blends data engineering with AI workloads, focusing on ingestion, transformation, quality assurance, lineage, and high-throughput data delivery to training jobs across modalities.

The ideal candidate has experience with petabyte-scale data systems, strong software engineering practices, and understands how data infrastructure

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