AI Data Engineer — Build Training Datasets in Azure

Experis (Austria); Redmond; Presencial; AUD 151.000 - 159.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Medical and Prescription Drug Plans

Dental Plan

Vision Plan

Health Savings Account

Health Flexible Spending Account

Dependent Care Flexible Spending Plan

Descripción de la vacante

Applied Sciences in Redmond, WA is seeking an AI Data Engineer to join our team. You will build and optimize Python data pipelines for ingestion, OCR processing, and data normalization to support confidential AI model training.

The role requires hands-on dataset-building experience from the ground up, strong Azure data management skills, and the ability to process large structured and unstructured data using memory-efficient techniques.

Formación

• Hands-on experience building datasets from the ground up.
• Five+ years of data-related experience.
• Python pipelines development, OCR processing, text extraction and data cleaning.
• Azure data management experience.
• Experience with large structured and unstructured datasets.

Responsabilidades

• Develop, maintain, and optimise Python data pipelines for ingestion and processing.
• Run and monitor large-scale batch jobs; implement retries.
• Build automated quality checks for data integrity.
• Prepare training-ready datasets via filtering and tokenisation.
• Manage Azure storage transfers and data synchronization.

Conocimientos

Data engineering

Python proficiency

Dataset building from ground up

Distributed processing techniques

Herramientas

Azure Blob Storage

Azure Data Lake Storage

SQL

Git

Linux

Pandas

NumPy

JSON/JSONL

CSV

Parquet

Command-line tools

Descripción del empleo

Applied Sciences in Redmond, WA is seeking an AI Data Engineer to join our team. You will build and optimize Python data pipelines for ingestion, OCR processing, and data normalization to support confidential AI model training.

The role requires hands-on dataset-building experience from the ground up, strong Azure data management skills, and the ability to process large structured and unstructured data using memory-efficient techniques.