ML Technology Intern, Graduate Students
CoStar Group is a leading global provider of commercial and residential real estate information and analytics. They are seeking a Machine Learning Intern to collaborate on improving their cloud-based machine learning environment and to design, build, train, and deploy machine learning models that enhance customer experience. Responsibilities Collaborate on the continued improvement of CoStar’s cloud-based machine learning environment Design, build, train, deploy and evaluate machine learning models that handle large amounts of data Collaborate with other engineers, product owners, and leadership to create ML solutions that solve practical problems and improve our customer’s experience Gain an understanding of the CoStar business and how ML can improve things Skills Must be currently enrolled full time in a Master's or PhD program in Computer Science, Computer Engineering, or a related field, or possess equivalent experience, with anticipated graduation between December 2026 and June 2027 Hands-on experience in developing and adapting algorithms for machine learning, as well as for image, text, multimodal data, or similar fields Professional experience as a Machine Learning Engineer, Data Scientist, or related role (for Master's candidates), or completion of 3+ relevant internships Strong programming skills in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn Experience deploying end-to-end ML solutions in cloud-based environments, including data ingestion, model training, evaluation, and inference Deep understanding of core ML concepts and ability to design custom solutions for practical problems Strong collaboration and problem-solving skills Experience with databases, such as DynamoDB, and cloud ML platforms, such as Databricks Company Overview CoStar Group (NASDAQ: CSGP) is the provider of commercial real estate information, analytics and marketing services. It was founded in 1987, and is headquartered in Arlington, Virginia, USA, with a workforce of 5001-10000 employees. Its website is