AI DataOps Engineer — Remote, Large-Scale Pipelines

Bright Vision Technologies; Chesterfield (MO); Remote; USD 150,000 - 165,000; Full time

Job summary

Bright Vision Technologies is seeking an AI Operations Engineer to design and operate large-scale data systems powering AI training and evaluation pipelines. You will drive ingestion, transformation, quality assurance, lineage, and high-throughput data delivery to training jobs across modalities.

The ideal candidate has 6+ years in data engineering for ML/AI, strong Python and JVM skills, and hands-on experience with Spark, Ray, or Beam, plus petabyte-scale storage and robust data workflows.

Qualifications

• Six or more years of data engineering experience in ML/AI workloads.
• Proficient in Python and at least one JVM language.
• Experience with petabyte-scale data systems and data pipelines.
• Strong understanding of distributed systems, data modeling, and storage formats.

Responsibilities

• 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 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.

Skills

Python

JVM language

Data engineering

Distributed systems

ML data pipelines

CI/CD

Communication

Testing

Tools

Spark

Ray

Beam

Job description

Bright Vision Technologies is seeking an AI Operations Engineer to design and operate large-scale data systems powering AI training and evaluation pipelines. You will drive ingestion, transformation, quality assurance, lineage, and high-throughput data delivery to training jobs across modalities.

The ideal candidate has 6+ years in data engineering for ML/AI, strong Python and JVM skills, and hands-on experience with Spark, Ray, or Beam, plus petabyte-scale storage and robust data workflows.