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Pennsylvania State University

Land-grant university in University Park, PA

Artificial Intelligence / Machine Learning Verification and Validation Engineer

Data ManagementConfirmed live in the last 24 hours
Full-time$92.1k - $200.8k

About the Job

Requirements

  • A Bachelor's degree in Computer Science, Data Science, Information Science, Engineering, or a related technical field is required.
  • Proficiency in Python and SQL for data manipulation, analysis, and pipeline development is required.
  • Familiarity with data annotation tools and workflows such as CVAT, Label Studio, or equivalent is required.
  • Understanding of machine learning concepts, including how data quality affects model training, evaluation, and deployment, is required.
  • For the Advanced Professional level, a Bachelor's degree in Engineering or Science and at least 5 years of relevant experience are required.
  • For the Intermediate Professional level, a Bachelor's degree in Engineering or Science and at least 2 years of relevant experience are required.
  • For the Professional level, a Bachelor's degree in Engineering or Science is required; no prior relevant work experience is required.
  • Must be eligible to obtain a government security clearance, participate in the ARL drug testing program, and comply with applicable electronic and physical monitoring requirements.
  • Must be a U.S. citizen to apply.

Responsibilities

  • Label, annotate, and curate multimodal datasets, including imagery/FMV, geospatial, signals, and 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 independent verification and validation 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 to make curated datasets discoverable and accessible to the research team.
  • Use Python, SQL, and annotation platforms such as CVAT and 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.

Desired Qualifications

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

About the Company

Pennsylvania State University

Land-grant university in University Park, PA

Pennsylvania State University is a multi-campus, land-grant public research university whose mission spans undergraduate and graduate education, research, and public service.

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