AI & Data Engineer: Build AI-Ready Data Pipelines

Mitchell Martin Inc.

Washington (District of Columbia)

Vor Ort

USD 150.000 - 160.000

Vollzeit

vor 38 Stunden
Sei unter den ersten Bewerbenden
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Zusammenfassung

Mitchell Martin Inc. in Washington, DC is seeking a Full-Time AI and Data Engineer to transform data architecture into robust production systems. The role focuses on building AI-ready data pipelines, retrieval systems, and reusable engineering patterns to enable AI applications across the enterprise.

You will collaborate with cross-functional teams, leverage AI platforms, and ensure data quality and observability while delivering scalable data products and analytics capabilities.

Qualifikationen

  • Bachelor's degree in computer science, data engineering, or related field.
  • 6 years of relevant technical experience, incl. AI/ML exposure.
  • Proficiency in Python and SQL; experience with distributed processing.
  • Experience with modern data stacks in cloud environments.

Aufgaben

  • Build and operate AI-ready data pipelines for data retrieval by AI applications.
  • Implement retrieval-augmented generation components and vector store integrations.
  • Develop interfaces for agents and copilots to safely query enterprise data.
  • Design and maintain production-grade data pipelines using modern tools.
  • Contribute to semantic models and data product development for analytics.

Kenntnisse

Python
SQL
AI/ML concepts
Data engineering

Ausbildung

Bachelor's degree in computer science, data engineering, information systems, or related field

Tools

ELT Tools
Distributed processing frameworks
Cloud platforms

Jobbeschreibung

Mitchell Martin Inc. in Washington, DC is seeking a Full-Time AI and Data Engineer to transform data architecture into robust production systems. The role focuses on building AI-ready data pipelines, retrieval systems, and reusable engineering patterns to enable AI applications across the enterprise.

You will collaborate with cross-functional teams, leverage AI platforms, and ensure data quality and observability while delivering scalable data products and analytics capabilities.

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