Remote AI Data Engineer: Scale Data Pipelines for ML

Bright Vision Technologies; Edison (NJ); Remote; USD 100,000 - 150,000; Full time

Job summary

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

The ideal candidate will have experience with petabyte-scale data systems, strong software engineering fundamentals, and an understanding

Qualifications

• 10+ years of data engineering experience supporting ML/AI workloads.
• Proficiency in Python and at least one JVM or systems language.
• Experience with Spark, Ray, or Beam.
• Hands-on with petabyte-scale storage and pipelines.
• Strong software engineering practices: testing, CI/CD, code reviews.

Responsibilities

• Design and operate large-scale AI data pipelines.
• Ingest data from multiple modalities (text, image, audio, video).
• Implement data cleaning, deduplication, and quality assurance at scale.
• Develop dataset versioning and lineage for reproducible training.
• Maximize GPU utilization with high-throughput data loading.
• Implement labeling and active learning workflows.
• Design storage architectures balancing cost and throughput.
• Build evaluation datasets with strict integrity controls.
• Ensure data privacy and consent throughout pipelines.
• Collaborate with ML researchers to align data needs.
• Monitor data quality, drift, and pipeline health.
• Document data systems and open-source tooling.

Skills

Python

Distributed systems

Data modeling

CI/CD

Spark

Ray

Beam

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 build and operate large-scale data systems powering AI training and evaluation pipelines. The role blends deep data engineering with a solid grasp of AI workloads, focusing on ingestion, transformation, quality assurance, lineage, and high-throughput data delivery to training jobs across modalities.

The ideal candidate will have experience with petabyte-scale data systems, strong software engineering fundamentals, and an understanding