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Data Engineering Specialist – AI

bright vision technologies·US·United States·mid
pythonsparkdata engineering
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Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. Job Title: Data Engineering Specialist – AI Location: 100% Remote Role Position Type: Full-time (Only W2 candidates) Salary Range: $100,000–$150,000 Annually Experience Required: 6+ years Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position. Job Summary We are seeking an Data Engineering Specialist – AI 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. Required Qualifications 6+ 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. Preferred Qualifications 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. Ho

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