AI Data Engineer

MACHINE LEARNING TECHNOLOGIES LLC; Phoenix (AZ); On-site; USD 74,000 - 105,000; Full time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC in Phoenix, AZ, is seeking an AI Data Engineer to design and maintain data architectures powering our AI/ML initiatives, including data pipelines for model training, retrieval-augmented generation (RAG), and production ML systems.

You will collaborate with ML engineers and data scientists to ensure data quality, governance, and lineage across pipelines, while optimizing for cost and performance and enabling secure access.

Qualifications

• Experience building data pipelines for AI/ML use cases.
• Experience handling structured and unstructured data.
• Knowledge of data governance and data lineage.

Responsibilities

• Design and build pipelines to ingest, clean, and transform structured and unstructured data (documents, PDFs, transcripts, logs) for AI/ML use cases
• Build and maintain vector embedding pipelines and support vector database integration
• Develop feature stores/pipelines for ML model training and inference
• Implement data pipelines supporting RAG architectures — chunking strategies, embedding refresh cycles, metadata tagging
• Partner with ML engineers/data scientists to understand data requirements for model training and evaluation
• Ensure data lineage, quality, and governance across pipelines feeding AI systems
• Optimize pipelines for cost and performance (e.g., Dynamic Tables, streaming ingestion)
• Support MLOps/LLMOps workflows — versioning datasets, tracking data used in model training for reproducibility and compliance
• Implement entitlement/access control logic so AI systems only access data they're authorized to use

Skills

SQL

Python

Scala

Airflow

dbt

Data governance

Unstructured data processing

Vector embeddings

RAG architectures

ML data lifecycle

Tools

Airflow

dbt

VectorDB

Job description

Job Overview

• Job ID: J53788
• Job Title: AI Data Engineer
• Location: Phoenix, AZ
• Duration: 12 Months + Extension
• Bill Rate: $65/hour
• Domain Exposure: Pharmaceuticals
• Client: To Be Discussed Later
• Employment Type: W-2, 1099, C2C
• Work Authorization: US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

We're looking for a Data Engineer to build and maintain the data infrastructure powering our AI/ML initiatives — including data pipelines for model training, retrieval-augmented generation (RAG), and production ML systems. This role sits at the intersection of data engineering and applied AI, ensuring high-quality, well-governed data is available for both traditional analytics and AI consumption.

Key Responsibilities

• Design and build pipelines to ingest, clean, and transform structured and unstructured data (documents, PDFs, transcripts, logs) for AI/ML use cases
• Build and maintain vector embedding pipelines and support vector database integration
• Develop feature stores/pipelines for ML model training and inference
• Implement data pipelines supporting RAG architectures — chunking strategies, embedding refresh cycles, metadata tagging
• Partner with ML engineers'/data scientists to understand data requirements for model training and evaluation
• Ensure data lineage, quality, and governance across pipelines feeding AI systems
• Optimize pipelines for cost and performance (e.g., Dynamic Tables, streaming ingestion)
• Support MLOps/LLMOps workflows — versioning datasets, tracking data used in model training for reproducibility and compliance
• Implement entitlement/access control logic so AI systems only access data they're authorized to use

Required Skills/Experience

• Strong SQL + one of Python/Scala for pipeline development
• Experience with a cloud data platform
• Experience with orchestration tools (Airflow, dbt)
• Understanding of embedding models, vector search, and RAG patterns
• Experience with unstructured data processing
• Familiarity with ML lifecycle concepts

Equal Opportunity Employer

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.