AI Engineer I

Key Responsibilities

• Design, develop, and train AI and machine learning models using a variety of techniques, including supervised, unsupervised, and deep learning approaches.
• Manipulate, analyze, and interpret large volumes of unstructured data from disparate sources to identify patterns, relationships, trends, and efficiencies.
• Perform model training, tuning, validation, and retraining, optimizing for accuracy and efficiency.
• Independently diagnose and resolve model performance issues, data quality problems, and algorithmic limitations.
• Design and implement experiments to evaluate model behavior, compare algorithms, and validate assumptions.
• Contribute to the overall architecture of AI systems, ensuring trained models integrate effectively with data pipelines, APIs, and downstream systems.
• Deploy trained models into production environments and perform ongoing monitoring and maintenance to ensure sustained performance.
• Collaborate with software engineers and technical stakeholders as needed to integrate trained models into operational systems.
• Continuously improve models using performance metrics, feedback, and evolving data.

• Bachelor’s degree in a computer science, computer engineering, or relevant field with focused education or professional experience in artificial intelligence or machine learning; a generic computer science background without AI/ML depth is not sufficient.
• Demonstrates hands-on experience training, evaluating, and refining machine learning or AI models.
• Strong understanding of machine learning algorithms, neural networks, optimization techniques, and model evaluation methods.
• Ability to work independently and manage complex technical tasks with minimal supervision while exercising wide latitude for professional judgment.
• U.S. Citizenship is required.

• Master’s degree in Artificial Intelligence, Machine Learning, Data Science, or a closely related field, with a thesis or significant project focused on AI/ML.
• Experience with pytorch and/or tensorflow libraries (project examples may be requested).
• Experience working with large, complex datasets.
• Familiarity with deploying and maintaining AI models in secure or regulated environments.