In This RoleYou will contribute to the development of AI training datasets by building and maintaining Python-based data processing pipelines. You will work with large-scale structured and unstructured datasets, transforming raw documents and text into high-quality, validated data for AI model training. This role requires hands-on experience creating datasets from the ground up, developing scalable data workflows, and managing data processing in Azure environments. You will collaborate with data scientists and engineering partners to improve data quality, processing efficiency, and dataset reliability while ensuring data integrity, traceability, and security.
Responsibilities- Design, develop, maintain, and optimize Python-based data pipelines for large-scale data ingestion, processing, and transformation.
- Build datasets from the ground up by collecting, organizing, cleaning, validating, and preparing raw structured and unstructured data.
- Develop workflows for OCR processing, text extraction, normalization, filtering, segmentation, and deduplication.
- Execute and monitor large-scale batch processing jobs, troubleshoot failures, and implement automated retry and recovery mechanisms.
- Develop automated data quality checks to identify missing or corrupted files, incomplete processing outputs, duplicate records, formatting issues, and metadata inconsistencies.
- Prepare high-quality, training-ready datasets through data filtering, tokenization, text segmentation, and conversion into standardized formats.
- Manage bulk data uploads, downloads, and synchronization between local processing environments and Azure storage platforms.
- Maintain organized datasets with consistent naming conventions, metadata, version control, and source traceability.
- Optimize data processing performance, memory utilization, storage efficiency, and cloud resource consumption.
- Monitor dataset statistics, processing coverage, quality metrics, and exceptions while generating operational reports.
- Collaborate with applied scientists and engineering teams to translate AI training requirements into scalable and repeatable data workflows.
- Maintain documented, tested, and version-controlled code while following established data security and governance requirements.
Qualifications- 5+ years of professional experience in data engineering, data pipeline development, or data science with substantial hands-on programming responsibilities.
- Strong proficiency in Python, including developing reusable modules, debugging, testing, logging, and error handling.
- Demonstrated experience building and developing datasets from scratch, including data ingestion, cleaning, transformation, validation, and preparation.
- Hands-on experience processing large-scale structured and unstructured datasets using memory-efficient, parallel, or distributed processing techniques.
- Practical experience with Azure Blob Storage or Azure Data Lake Storage, including bulk data transfers, storage organization, and access troubleshooting.
- Experience with Python data-processing libraries and formats such as pandas, NumPy, JSON/JSONL, CSV, and Parquet.
- Working knowledge of SQL, Git, Linux environments, and command-line tools.
- Strong troubleshooting, analytical, and problem-solving skills with a focus on data quality and integrity.
- Ability to communicate technical challenges and collaborate effectively with cross-functional engineering and data science teams.
Preferred Qualifications- Experience developing OCR pipelines, processing scanned documents, multilingual text, or document-layout data.
- Experience with Azure Databricks, Azure Machine Learning, Azure Data Factory, or other workflow orchestration platforms.
- Familiarity with Hugging Face Datasets, AI/ML tokenization, near-duplicate detection, and training/evaluation data separation.
- Experience with large-scale dataset curation and preparation for AI or machine learning model training.
- Knowledge of distributed data processing frameworks and technologies such as PySpark.
- Experience with dataset lineage, reproducibility, containerized environments, and CI/CD practices.
- Experience optimizing data pipelines for performance, reliability, scalability, and cost efficiency.
Salary RangeAt Blueprint, we strive to offer competitive pay that reflects the value of our team members. Compensation for this role is influenced by a variety of factors, including skills, education, responsibilities, experience, and geographic market. For candidates based in Washington State, the anticipated salary range is
$150,000- $160,000 USD/Annually. Please note that we typically do not hire new employees at the top of the posted range. Actual starting pay will be determined based on experience, skills, and internal equity. The final salary and job title may vary depending on the selected candidate's qualifications and could fall outside the stated range.
Blueprint believe in the importance of a healthy and happy team, which is why our comprehensive benefits package includes:
- Medical, dental, and vision coverage
- Flexible Spending Account
- 401k program
- Competitive PTO offerings
- Parental Leave
- Opportunities for professional growth and development
Location: 5 days onsite at Seattle, WA
BenefitsBlueprint believes that healthy, supported employees do their best work. Eligible employees have access to a comprehensive benefits package that may include:
- Medical, dental, and vision coverage
- Flexible Spending Account (FSA)
- 401(k) retirement plan
- Competitive paid time off
- Parental leave
- Professional growth and development opportunities
Benefits and eligibility may vary based on role, employment status, and location.
