The American Institutes for Research (AIR) is a leading professional services firm with a growing software engineering and product development team. For nearly 70 years, we have designed, developed, and implemented large-scale assessment programs for states across the country with powerful results. AIR Assessment fuses statistics, technology, and content into powerful formative, summative, adaptive, alternate, and diagnostic assessments. These assessments help students learn, teachers teach, and parents know what is happening at school.
Our years of work and experience in software design and development has positioned us as a leader in the online testing industry and provided us the opportunity to make a positive difference in the educational systems that impact millions of students across the nation. During the 2017-2018 school year alone, AIR delivered nearly 50 million online tests.
Some of our ground-breaking work includes:
• Design and development of large-scale state assessment services
• Development of next-generation classroom products
• Advanced computer-adaptive algorithms (only one that’s peer-approved in the country)
• Mobile support for the user interfaces
• Learning management systems with social media features
• User interfaces that are universally accessible to people with or without disabilities
• Innovative, machine-scorable items
• Business Intelligence and Machine Learning
We are currently seeking Machine Learning Interns to join our Washington, DC office for the summer. The ideal candidate will start in May and work fulltime through mid-August.
• Implement and inform a project that is focused on improving some aspect of our machine learning software or methods.
• Write code in Python using machine learning frameworks and libraries to ingest and clean data, build models, and evaluate results
• Document, archive, and present work on the project
• Work as part of a multi-disciplinary team discussing methods and results of this project and others
• Level: Master’s or Ph.D. degree in progress.
• Coursework in Computer Science, Mathematics, Computational Linguistics or similar field
• Experience with engine calibration methods (e.g., sampling, pipeline, analysis)
• Course and/or work-based experience with machine learning models including multi-layer neural nets, natural language processing (NLP) methods (e.g., text handling, grammars, corpora use, latent semantic analysis; entity recognition), and in the evalution of engine performance
• Coding ability with Python, machine learning frameworks (e.g., Keras, PyTorch) and related libraries for machine learning (e.g., scikit-learn) and NLP (NLTK, spaCy)
• Strong communication skills and ability to work with others
• An analytical mind with problem-solving abilities