3 дня назад
ML Data Engineer (AI)
100 000 - 150 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
ML Data Engineer (AI): Building and operating large-scale data systems for AI training and evaluation pipelines with an accent on data ingestion, transformation, quality assurance, lineage, and high-throughput delivery. Focus on petabyte-scale storage, distributed data processing, dataset reproducibility, and efficient data loading for accelerator-based training.
Location: 100% remote within the United States
Salary: $100,000–$150,000 annually
Company
is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.
What you will do
- Build and operate large-scale data systems powering AI training and evaluation pipelines.
- Develop ingestion and transformation workflows for diverse data modalities.
- Ensure data quality, lineage, versioning, and reproducibility across ML workflows.
- Deliver high-throughput datasets to accelerator-based training jobs.
- Operate petabyte-scale storage and pipeline systems.
- Collaborate cross-functionally while applying testing, CI/CD, and code review practices.
Requirements
- Bachelor’s or Master’s degree in Computer Science or a related field.
- 6+ years of data engineering experience, including significant work supporting ML or AI workloads.
- Strong Python proficiency and experience with at least one JVM or systems language.
- Deep experience with Spark, Ray, or Beam and hands-on experience with petabyte-scale data systems.
- Strong understanding of distributed systems, data modeling, and storage formats.
- Applicants must be U.S. Citizens, Green Card Holders, EAD Holders, or H-1B transfer candidates; new H-1B visa petitions cannot be sponsored.
Nice to have
- Experience with large-scale multimodal datasets and frontier model training pipelines.
- 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.
Culture & Benefits
- Full-time direct W2 employment.
- Remote work within the United States.
- Career growth opportunities within an established organization.
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