The AI/ML Data Engineer will design, build, and maintain data infrastructure supporting artificial intelligence and machine learning initiatives, including model training, retrieval-augmented generation (RAG), and production ML systems. This role will develop reliable pipelines for structured and unstructured data while supporting vector search, feature engineering, data governance, and MLOps workflows. The ideal candidate combines strong data engineering skills with practical knowledge of AI/ML data architectures and emerging AI technologies., * Design and build pipelines to ingest, clean, transform, and prepare structured and unstructured data for AI/ML use cases.

• Process documents, PDFs, transcripts, logs, and other unstructured data sources.
• Build and maintain vector embedding pipelines and support vector database integrations.
• Develop feature pipelines and data infrastructure supporting ML model training and inference.
• Implement data pipelines supporting RAG architectures, including chunking strategies, embedding refresh cycles, and metadata tagging.
• Partner with ML engineers and data scientists to understand data requirements for model training, evaluation, and deployment.
• Implement and maintain data quality, lineage, governance, and monitoring across pipelines supporting AI systems.
• Optimize data pipelines for cost, scalability, reliability, and performance.
• Support streaming ingestion and modern data platform capabilities, including dynamic or incremental data processing.
• Support MLOps and LLMOps workflows, including dataset versioning and tracking data used for model training and evaluation.
• Implement data entitlement and access control logic to ensure AI systems only access authorized data.
• Contribute to reproducible and compliant AI/ML data workflows.

• Strong SQL skills and proficiency in Python or Scala for data pipeline development.
• Experience developing and maintaining data pipelines in a cloud-based data platform.
• Experience with data orchestration and transformation tools such as Airflow or dbt.
• Understanding of embedding models, vector search, and retrieval-augmented generation (RAG) architectures.
• Experience processing and transforming unstructured data.
• Familiarity with machine learning lifecycle concepts, including training, evaluation, deployment, and data management.
• Strong understanding of data quality, lineage, governance, and access controls.
• Ability to collaborate effectively with data scientists, ML engineers, and other technical stakeholders.

Education

• Bachelor’s degree in Computer Science, Data Engineering, Computer Engineering, or a related technical field preferred.

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We offer a comprehensive benefits package to our employees, which includes:

• Medical Insurance
• Vision & Dental Insurance
• Life Insurance
• Matching 401(k)
• Commuter Benefits
• Employee Discounts & Rewards
• Payroll Payment Options

Equiliem believes in empowering success. It’s our job to cultivate relationships that connect people and employers in a way that is inclusive, intelligent, and allows both to thrive.

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For almost 30 years, we’ve helped shape our industry. Today, we continue to research, ask questions, and continuously enhance the candidate journey and client experience.