AI Data Engineer

Bright Vision Technologies
Parsippany-Troy Hills, United States of America
3 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 150K

Job location

Remote
Parsippany-Troy Hills, United States of America

Tech stack

Artificial Intelligence
Big Data
Code Review
Continuous Integration
Data Cleansing
Data Deduplication
Information Engineering
Data Infrastructure
ETL
Data Systems
Distributed Systems
Document-Oriented Databases
Java Virtual Machine (JVM)
Python
Open Source Technology
Software Engineering
Management of Software Versions
Data Processing
Spark
Caching
Storage Technologies
Information Technology
Integration Frameworks
Free and Open-Source Software
Machine Learning Operations
Data Pipelines

Job description

This role is part of Bright Vision Technologies' 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. We do not engage in C2C, 1099, or third-party arrangements for this role. BUT STRICTLY NO C2C/1099/3RD PARTY COMPANIES. ALL OUR ROLES ARE W2 AND NO 3RD PARTY BROKERING PLEASE. Candidates must be willing to work directly as a full-time W2 employee of Bright Vision Technologies and contribute to our in-house SOW deliverables. No new H1B sponsorship is available for this role. However, candidates who are currently on a valid H1B visa and require a transfer are welcome to apply. We will support H1B transfers for qualified candidates. For every role, a technical coding assessment is mandatory. Please apply only if you are confident in your technical abilities and hands-on experience. Job Summary 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. The ideal candidate has experience operating petabyte-scale data systems, strong software engineering fundamentals, and clear understanding of how data infrastructure choices propagate into model quality and training efficiency., * 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.

Requirements

  • 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.

Benefits & conditions

Position Type: In-house Bright Vision Technologies SOW engagement (no third-party client or vendor) Salary: $100K - $150K / Annum Experience: 6+ years Sponsorship: No new H1B sponsorship available. H1B transfers welcomed for qualified candidates. Employment Type: Full-time, direct W2 with Bright Vision Technologies (no C2C, no 1099, no third-party) Engagement: Long-term, multi-year, aligned to the Bright Vision SOW delivery roadmap Compensation: Competitive base salary commensurate with experience, plus benefits. Employment Terms & Visa Policy

About the company

Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications.

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