Remote AI Data Engineer - Scale-Pipeline Specialist

Bright Vision Technologies; United States; Remote; USD 80,000 - 100,000; Full time

Job summary

Bright Vision Technologies is seeking an AI Data Engineer to design and operate large-scale data pipelines powering AI training and evaluation. This remote role focuses on ingestion, transformation, quality assurance, lineage, and high-throughput data delivery for diverse modalities.

Ideal candidates have 6+ years in data engineering, strong Python and at least one JVM language, and hands-on experience with Spark, Ray, or Beam, plus petabyte-scale storage and robust CI/CD practices.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related field.
• 6+ years data engineering experience with ML/AI workloads.
• Proficient in Python and at least one JVM language.
• Deep experience with Spark, Ray, or Beam.
• Experience operating petabyte-scale storage and pipelines.
• 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 modeling

Dataset versioning & lineage

Testing & CI/CD

Communication & collaboration

Education

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

Tools

Spark

Ray

Beam

Job description

Bright Vision Technologies is seeking an AI Data Engineer to design and operate large-scale data pipelines powering AI training and evaluation. This remote role focuses on ingestion, transformation, quality assurance, lineage, and high-throughput data delivery for diverse modalities.

Ideal candidates have 6+ years in data engineering, strong Python and at least one JVM language, and hands-on experience with Spark, Ray, or Beam, plus petabyte-scale storage and robust CI/CD practices.