AI Data Engineer

Employment Terms & Visa Policy

This is a 100% remote, full-time, direct W2 position with Bright Vision Technologies. The role is part of an in‑house Statement of Work (SOW) engagement. The client, end customer, and employer for this position is Bright Vision Technologies – there is no third‑party client, vendor, or implementation partner involved.

No new H1B sponsorship is available. H1B transfers are welcomed for qualified candidates.

We do not engage in C2C, 1099, or third‑party arrangements for this role.

We are seeking an AI Data Engineer to build and operate the large‑scale data systems that power modern AI training and evaluation pipelines. The role combines deep data engineering expertise with a strong understanding of AI workloads, focusing on ingestion, transformation, quality assurance, lineage, and high‑throughput delivery of data to training jobs across diverse modalities.

• Design and operate large‑scale data pipelines supporting AI training, evaluation, and continual improvement workflows.
• Build ingestion systems for diverse modalities including text, image, audio, video, and structured signals.
• Implement data cleaning, deduplication, filtering, and quality assurance at petabyte scale.
• Develop dataset versioning, lineage, and provenance tracking systems suitable for reproducible training.
• Build high‑throughput data loading systems that maximize GPU utilization during training.
• Implement labeling workflows, active learning pipelines, and human‑in‑the‑loop data improvement systems.
• Design storage architectures balancing cost, throughput, and latency across data tiers.
• Build evaluation dataset construction pipelines with strict integrity and contamination controls.
• Implement data privacy, redaction, and consent enforcement throughout the pipeline.
• Collaborate with ML researchers and engineers to align data systems with model development needs.
• Drive observability of data quality, drift, and pipeline health across the AI data estate.
• Optimize cost and performance through compression, format selection, and caching strategies.
• Document data systems, schemas, and operational procedures for broad internal use.
• Stay current with AI data infrastructure research and emerging open‑source tools.

• Bachelor’s or Master’s degree in Computer Science or a related field.
• Six or more years of data engineering experience, with significant work supporting ML or AI workloads.
• Strong proficiency in Python and at least one JVM or systems language.
• Deep experience with modern data processing frameworks such as Spark, Ray, or Beam.
• Hands‑on experience operating petabyte‑scale storage and pipeline systems.
• 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.

• Experience with multimodal datasets at large scale.
• Familiarity with data quality tooling and dataset evaluation methodology.
• Exposure to privacy‑preserving data systems and regulated data handling.
• Open‑source contributions to data infrastructure projects.
• Experience supporting frontier model training pipelines.

For immediate consideration, please send your resume to  Learn more about Bright Vision Technologies at

We recognize that our people are our strength, and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company.

We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental…