Remote AI Pipeline Engineer - Petabyte-Scale Data

Bright Vision Technologies; Maple Grove (MN); Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking an AI Pipeline Engineer to design and operate large-scale data systems powering AI training and evaluation pipelines. This role emphasizes ingestion, transformation, quality assurance, lineage, and high-throughput data delivery for multi-modal workloads.

You will collaborate with ML researchers and engineers to optimize data infrastructure, ensure reproducibility, and maximize GPU utilization, while maintaining data privacy and governance in a remote-first

Qualifications

• Bachelor's or Master's degree in Computer Science or related field.
• 6+ years of data engineering experience with ML/AI workloads.
• Strong Python and at least one JVM or systems language.
• Experience with Spark, Ray, or Beam and petabyte-scale data pipelines.
• Understanding of distributed systems, data modeling, and reproducibility.

Responsibilities

• Design and operate large-scale data pipelines for AI training and evaluation.
• Build ingestion systems for text, image, audio, video, and structured data.
• Implement cleaning, deduplication, filtering, and QA at petabyte scale.
• Develop dataset versioning, lineage, and provenance for reproducible training.
• Maximize GPU utilization with high-throughput data loading systems.
• Create labeling workflows and active learning pipelines with human-in-the-loop.
• Design storage architectures balancing cost, throughput, and latency.
• Ensure data privacy, redaction, and consent enforcement throughout pipelines.
• Collaborate with ML researchers to align data systems with model needs.
• Drive observability of data quality, drift, and pipeline health.

Skills

Data engineering

Python

Distributed systems

Communication

CI/CD

Education

Bachelor's or Master's in CS

Tools

Spark

Ray

Beam

Job description

Bright Vision Technologies is seeking an AI Pipeline Engineer to design and operate large-scale data systems powering AI training and evaluation pipelines. This role emphasizes ingestion, transformation, quality assurance, lineage, and high-throughput data delivery for multi-modal workloads.

You will collaborate with ML researchers and engineers to optimize data infrastructure, ensure reproducibility, and maximize GPU utilization, while maintaining data privacy and governance in a remote-first