AI Data Engineer (AI Training Data)

Location: 5 days onsite in Seattle, WA; other listed locations include Redmond, WA, and Bellevue, WA.

Salary: $150,000–$160,000 USD annually for candidates based in Washington State.

Company

hirify.global is a technology solutions firm delivering AI, cloud, data, product development, and emerging technology services.

What you will do

• Design, develop, maintain, and optimize Python pipelines for large-scale data ingestion, processing, and transformation.
• Build training datasets from raw structured and unstructured data through collection, cleaning, validation, filtering, tokenization, segmentation, and standardized conversion.
• Develop OCR, text extraction, normalization, filtering, segmentation, deduplication, and automated data-quality workflows.
• Execute and monitor batch-processing jobs, troubleshoot failures, and implement retry and recovery mechanisms.
• Manage Azure storage transfers, dataset organization, metadata, version control, source traceability, and operational reporting.
• Collaborate with applied scientists and engineering teams to create scalable, repeatable AI data workflows while maintaining security and governance.

Requirements

• 5+ years of professional experience in data engineering, data pipeline development, or data science with substantial hands-on programming.
• Strong Python proficiency, including reusable modules, debugging, testing, logging, and error handling.
• Demonstrated experience building datasets from scratch, including ingestion, cleaning, transformation, validation, and preparation.
• Experience processing large-scale structured and unstructured datasets with memory-efficient, parallel, or distributed techniques.
• Practical experience with Azure Blob Storage or Azure Data Lake Storage, including bulk transfers, storage organization, and access troubleshooting.
• Experience with pandas, NumPy, JSON/JSONL, CSV, and Parquet.
• Working knowledge of SQL, Git, Linux, and command-line tools.
• Strong troubleshooting, analytical, and problem-solving skills focused on data quality and integrity.
• Ability to communicate technical challenges and collaborate with engineering and data science teams.

Nice to have

• Experience with OCR pipelines, scanned documents, multilingual text, or document-layout data.
• Experience with Azure Databricks, Azure Machine Learning, Azure Data Factory, or workflow orchestration platforms.
• Familiarity with Hugging Face Datasets, AI/ML tokenization, near-duplicate detection, and training/evaluation data separation.
• Experience curating large-scale datasets for AI or machine learning model training.
• Knowledge of distributed processing technologies such as PySpark.
• Experience with dataset lineage, reproducibility, containers, CI/CD, and performance, reliability, scalability, or cost optimization.

Culture & Benefits

• Onsite work is required five days per week in Seattle, Washington.
• Medical, dental, and vision coverage, subject to eligibility.
• Flexible Spending Account and 401(k) retirement plan.
• Competitive paid time off and parental leave.
• Professional growth and development opportunities.