Remote AI Data Engineer - Scalable Data Pipelines

Bright Vision Technologies; Cranberry Township (Butler County); Remote; USD 100,000 - 150,000; 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 in a fully remote role. You will own ingestion, transformation, quality assurance, and provenance for petabyte-scale datasets across modalities.

The ideal candidate has 10+ years in data engineering, strong Python, JVM language experience, and hands-on expertise with Spark/Ray/Beam, streaming and storage systems, and reproducible ML workflows.

Qualifications

• 10+ years of data engineering experience, with ML/AI workloads.
• Strong Python and at least one JVM or systems language.
• Experience with data processing frameworks (Spark, Ray, Beam).
• Hands-on with petabyte-scale storage and pipelines.
• Knowledge of data modeling, provenance, and reproducibility.

Responsibilities

• Design and operate large-scale data pipelines for AI training and evaluation.
• Build ingestion systems for multimodal data (text, images, audio, video).
• Implement data cleaning, deduplication, and quality assurance at scale.
• Develop dataset versioning, lineage, and provenance tracking.
• Create high-throughput loading to maximize GPU utilization.
• Develop labeling workflows and active learning pipelines.
• Design cost-efficient storage architectures across data tiers.
• Ensure data privacy and consent enforcement throughout pipelines.
• Collaborate with ML researchers and engineers to meet model needs.
• Monitor data quality and pipeline health across the estate.

Skills

Python

Java/Scala

Distributed systems

CI/CD

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 in a fully remote role. You will own ingestion, transformation, quality assurance, and provenance for petabyte-scale datasets across modalities.

The ideal candidate has 10+ years in data engineering, strong Python, JVM language experience, and hands-on expertise with Spark/Ray/Beam, streaming and storage systems, and reproducible ML workflows.