Machine Learning Data Engineer

Company: BV Teck

Location: Remote (Remote)

Salary: $100,000 - $150,000 a year

Type: Full-time

Remote: Yes

Posted: 2026-07-17

About this role

Machine Learning Data Engineer – Remote

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: Machine Learning Data Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
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 Machine Learning 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.

Key Responsibilities

  • 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 lear...

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