AI Data Engineer - Build AI-Ready Pipelines & MLOps

MACHINE LEARNING TECHNOLOGIES LLC; Phoenix (AZ); In loco; USD 74.000 - 105.000; Tempo pieno

Descrizione del lavoro

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.

Competenze

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

Mansioni

• 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

Conoscenze

SQL

Python

Scala

Airflow

dbt

Data governance

Unstructured data processing

Vector embeddings

RAG architectures

ML data lifecycle

Strumenti

Airflow

dbt

VectorDB

Descrizione del lavoro

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.