Artificial Intelligence / Machine Learning Verification and Validation Engineer

Penn State University•University Park, IL

5d•$92,100 - $200,808•Onsite

About The Position

We are searching for a talented, experienced, organized, detail-oriented, and highly motivated AI/ML Engineer to join our Independent Verification and Validation (IV&V) and Data Curation Center of Excellence in the Information Science Division within the All-Domain Analytics and Signatures Office (A2SO) at the Applied Research Laboratory (ARL). This team serves as the foundation for effective machine learning—building, curating, and governing the data that directly determines whether AI/ML models succeed in operationally relevant environments. You will focus on hands-on work with classified multi-modal data, including imagery/FMV, geospatial and AIS tracks, signals and sensor data, and text-based intelligence reports and develop pipelines, annotation frameworks, and quality assurance processes while gaining deep exposure to state-of-the-art AI/ML research. ARL is an authorized DoD Skillbridge partner and welcomes all transitioning military members to apply.

Requirements

Bachelor's Degree in Computer Science, Data Science, Information Science, Engineering, or a related technical field
Proficiency in Python and SQL for data manipulation, analysis, and pipeline development
Familiarity with data annotation tools and workflows (e.g., CVAT, Label Studio, or equivalent)
Understanding of machine learning concepts, including how data quality impacts model training, evaluation, and deployment

Nice To Haves

Experience working with DoD or Intelligence Community data, workflows, or operational environments
Familiarity with geospatial data formats (shapefiles, GeoJSON, AIS), imagery/FMV exploitation, or signals data processing
Experience with data versioning tools (e.g., DVC, LakeFS) or data catalog platforms
Knowledge of IV&V methodologies and quality assurance practices for data-driven systems
Exposure to containerized development environments (Docker, Kubernetes) and cloud platforms (AWS, Azure)
Current eligibility for access to classified information at the TS/SCI level or higher and may be subject to a government background investigation to upgrade clearance eligibility, if required

Responsibilities

Label, annotate, and curate multi-modal datasets (imagery/FMV, geospatial, signals, text/documents) to support AI/ML model development and evaluation
Design and implement data pipelines for ingestion, transformation, quality control, and cataloging of classified and open-source data
Develop and maintain annotation standards, labeling guidelines, and data governance processes to ensure consistency and reproducibility across projects
Conduct IV&V of datasets and model outputs to ensure data integrity, label accuracy, and fitness for intended use
Collaborate with research scientists, algorithm developers, and program stakeholders to identify, acquire, and prioritize data requirements for specific AI/ML projects
Build and maintain data catalogs, metadata schemas, and access-controlled repositories that make curated datasets discoverable and accessible to the broader research team
Employ Python, SQL, and annotation platforms (e.g., CVAT, Label Studio) to automate labeling workflows, perform exploratory data analysis, and develop quality metrics
Document data provenance, lineage, and known limitations to support model evaluation, reproducibility, and responsible AI practices
Collaborate within an Agile development environment as part of a large research team