IV&V AI/ML Data Quality Engineer (Multi-Modal)

The Pennsylvania State University; Reston (VA); On-site; USD 111,000 - 241,000; Full time

Benefits offered by this job

75% tuition discount

Competitive benefits package

Job summary

The Pennsylvania State University’s Applied Research Laboratory (ARL) is seeking an experienced AI/ML Engineer to join the IV&V and Data Curation Center of Excellence within the All-Domain Analytics and Signatures Office. This role focuses on building and governing data pipelines for multi-modal, including imagery, geospatial, signals, and text data, to support robust ML model development.

You will annotate, curate, and validate datasets, develop data catalogs and provenance documentation,

Qualifications

• Bachelor's Degree in a technical field is required.
• Proficiency in Python and SQL for data manipulation and pipelines.
• Familiarity with data annotation tools and workflows (CVAT, Label Studio).
• Understanding of ML concepts and data quality impacts on models.

Responsibilities

• Label, annotate, and curate multi-modal datasets to support AI/ML development.
• Design data pipelines for ingestion, transformation, and cataloging of data.
• Develop/maintain annotation standards and data governance processes.
• Conduct IV&V of datasets and model outputs to ensure data integrity.
• Collaborate with researchers to identify data requirements and priorities.
• Build data catalogs, metadata schemas, and access-controlled repositories.
• Use Python, SQL, and annotation platforms to automate labeling and analyses.
• Document data provenance and known limitations for reproducibility.

Skills

Python

SQL

CVAT

Label Studio

ML concepts

Agile

Education

Bachelor's Degree in Computer Science, Data Science, Information Science, Engineering, or a related technical field

Tools

Docker

Kubernetes

AWS

Azure

Job description

The Pennsylvania State University’s Applied Research Laboratory (ARL) is seeking an experienced AI/ML Engineer to join the IV&V and Data Curation Center of Excellence within the All-Domain Analytics and Signatures Office. This role focuses on building and governing data pipelines for multi-modal, including imagery, geospatial, signals, and text data, to support robust ML model development.

You will annotate, curate, and validate datasets, develop data catalogs and provenance documentation,