AI/ML Computer Science Research and Development Engineer

The Pennsylvania State University•University Park, FL

5d•Onsite

About The Position

Penn State’s Applied Research Laboratory (ARL) is seeking a highly motivated researcher for its Comprehensive Software Solutions (CSS) Department. CSS uses a broad range of software concepts, techniques, and languages to solve challenging problems for ARL sponsors and internal needs. The role focuses on innovative research and transitioning concepts into technical capabilities, particularly in artificial intelligence, machine learning, deep learning, and generative AI, with an emphasis on adversarial, safe, and/or agentic AI. ARL supports the Navy, the Department of Defense, and the Intelligence Community by researching and developing solutions to scientific, engineering, and technology problems. The position is fully onsite in State College, Pennsylvania, and may require periodic travel to remote locations for testing. The role may be filled at either the Senior Professional level, requiring a bachelor’s degree in Engineering or Science and 14 or more years of relevant experience, or the Advanced Professional level, requiring the same degree and at least 5 years of relevant experience. No certifications are required. Applicants must be U.S. citizens and eligible to obtain a government security clearance. Employment also requires successful completion of background checks and participation in ARL’s drug-testing program, along with compliance with electronic and physical monitoring requirements for federal contractors.

Requirements

Bachelor’s degree in Engineering or Science.
At least 5 years of relevant experience for the Advanced Professional level, or at least 14 years for the Senior Professional level.
Strong foundation in supervised, unsupervised, and reinforcement learning.
Hands-on model development using frameworks such as PyTorch, TensorFlow, or JAX.
Proficiency in Python and scientific computing libraries such as NumPy, Pandas, and SciPy.
Experience with data preprocessing, feature engineering, and structured and unstructured datasets.
Solid understanding of statistics, probability, optimization, and linear algebra.
Ability to design and implement deep neural networks, including CNNs, RNNs, or Transformer-based architectures.
Familiarity with training and evaluating models on GPU-accelerated hardware.
Ability to integrate AI/ML models into software systems or prototypes.
Knowledge of model validation, benchmarking, and performance-tuning practices.
Strong problem-solving skills and ability to translate research questions into practical ML tasks.
Knowledge of version control, testing, and modern software engineering practices.
Ability to communicate technical concepts clearly to interdisciplinary teams.
Demonstrated record of AI/ML research, publications, or impactful project contributions.
U.S. citizenship and eligibility to obtain a government security clearance.
Successful completion of required background checks and participation in ARL’s drug-testing program; compliance with applicable electronic and physical monitoring requirements.

Nice To Haves

Master’s or doctorate in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Mathematics, or a closely related field.
Experience in explainable AI, trustworthy AI, or robust/adversarial ML.
Background working with large-scale datasets, streaming data, or multimodal sensor data.
Experience with Docker, containerized ML services, or ML pipeline tools.
Experience in applied research environments or mission-focused systems development.
Current eligibility for access to classified information at the TS/SCI level or higher.

Responsibilities

Conduct advanced research in AI/ML, software engineering, computational systems, or related fields.
Develop novel methods, models, and technologies to address emerging AI challenges relevant to ARL sponsors.
Communicate results through technical reports, publications, and presentations to stakeholders, scientists, software engineers, and external sponsors.
Contribute to publications, white papers, technical memoranda, and study plans, especially in AI/ML.
Collaborate with interdisciplinary teams to design, prototype, and evaluate mission-focused solutions.
Perform larger tasks individually or as part of a group, and lead tasks.
Develop and integrate AI/ML models into software systems or prototypes.
Build reproducible experiments and maintain clear documentation.
Validate, benchmark, and tune model performance.