Senior AI Data Platform Engineer

Bright Vision Technologies; United States; Remote; USD 150,000 - 165,000; Full time

Job summary

Bright Vision Technologies is seeking an AI Operations Engineer to build and operate large-scale data systems powering modern AI training and evaluation pipelines. The role blends data engineering with deep AI workload understanding, focusing on ingestion, transformation, quality assurance, lineage, and high-throughput data delivery to training jobs across modalities.

The ideal candidate has 6+ years of experience, strong Python skills, and hands-on experience with Spark, Ray, or Beam, plus

Qualifications

• 6+ years of data engineering experience, with ML/AI workloads.
• Strong proficiency in Python and at least one JVM language.
• Experience with data processing frameworks Spark, Ray or Beam.
• Experience operating petabyte-scale data systems.

Responsibilities

• Build and operate large-scale data systems powering AI training and evaluation pipelines.
• Ensure ingestion, transformation, quality assurance, and data lineage.
• Deliver high-throughput data to training jobs across diverse modalities.
• Collaborate with software engineering and data teams to optimize pipelines.
• Apply testing, CI/CD, and code review best practices.
• Maintain data quality and reproducibility for ML workflows.
• Support cross-functional stakeholders with data intelligence.
• Architect scalable data infrastructure to improve training efficiency.

Skills

Python

Distributed systems

Data engineering

CI/CD

Communication

Tools

Spark

Ray

Beam

Job description

Bright Vision Technologies is seeking an AI Operations Engineer to build and operate large-scale data systems powering modern AI training and evaluation pipelines. The role blends data engineering with deep AI workload understanding, focusing on ingestion, transformation, quality assurance, lineage, and high-throughput data delivery to training jobs across modalities.

The ideal candidate has 6+ years of experience, strong Python skills, and hands-on experience with Spark, Ray, or Beam, plus