数据工程专员 – AI
Data Engineering Specialist – AI
Bright Vision Technologies 是一家技术咨询和软件开发公司，为美国各地提供云、AI、数据和企业解决方案。加入一家知名且备受尊敬的组织，这是一个绝佳的机会，提供巨大的职业发展潜力。
职位名称：数据工程专家 – AI
地点：100% 远程职位
职位类型：全职（仅限 W2 候选人）
薪资范围：每年 10 万至 15 万美元
所需经验：6 年以上
赞助：美国公民、绿卡持有者、EAD 持有者和 H-1B 转移候选人欢迎申请。我们无法为该职位申请新的 H-1B 签证。
职位简介
我们正在寻找一名数据工程专家 – AI 来构建和运营支撑现代 AI 训练和评估流程的大规模数据系统。该职位结合了深厚的数据工程专业知识与对 AI 工作负载的深刻理解，专注于数据摄取、转换、质量保证、数据血缘以及跨多种模态的数据高吞吐量交付。理想的候选人具备操作 PB 级数据系统的经验，扎实的软件工程基础，并清楚了解数据基础设施选择如何影响模型质量和训练效率。
所需资格
· 6 年以上数据工程经验，有支持 ML 或 AI 工作负载的显著经验。
- 精通 Python 和至少一种 JVM 或系统语言。
- 对现代数据处理框架如 Spark、Ray 或 Beam 有深入经验。
- 有操作 PB 级存储和管道系统的实际经验。
优先考虑的资格
· 在大规模多模态数据集方面有经验。
- 熟悉数据质量工具和数据集评估方法。
- 了解隐私保护数据系统和受监管的数据处理。
- 参与数据基础设施项目的开源贡献。
- 支持前沿模型训练流程的经验。
申请方式
您是否想了解更多关于这个机会的信息？
如需立即考虑，请将简历发送至或致电联系我们 (908) 505-3545。在 www.bvteck.com 了解更多关于 Bright Vision Technologies 的信息。
Bright Vision Technologies 是平等就业机会雇主。平等就业机会（EEO）声明
Bright Vision Technologies（BV Teck）致力于为所有员工和申请人提供平等的就业机会（EEO），不因种族、肤色、性别、宗教、国籍、年龄、残疾或退伍军人身份而有所区别。
查看英文原文
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.
How to Apply
Would you like to know more about this opportunity?
For immediate consideration, please send your resume to or contact us at (908) 505-3545. Learn more about Bright Vision Technologies at www.bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer.Equal Employment Opportunity (EEO) Statement
Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.
BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.
Originally posted on Himalayas