Nuuly is seeking a Machine Learning Engineer to join our team! The URBN Machine Learning Engineering Team is part of the URBN Data Science organization and is responsible for the Data Science, Machine Learning, Analytics, and Reporting functions at Nuuly, a subscription-based apparel rental service. Our team functions as a full-service Machine Learning provider, managing projects from ideation and requirements through to production deployment. Nuuly’s state-of-the-art Kafka-based streaming data platform enables real-time data access and offline capabilities, supporting flexible and iterative model development to power personalization, inventory forecasting, and dynamic pricing.
As a Machine Learning Engineer, your primary focus will be building and maintaining ML model training and evaluation pipelines and production services for a new personalization system. Responsibilities will include:
Experience with any of the following is a plus, but not required:
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URBN offers comprehensive Perks & Benefits to employees. Availability and eligibility to specific benefits may be subject to your location and employment status. Benefits include medical, dental, vision, PTO, generous employee discounts, retirement savings and much more! For additional information visit www.urbn.com/work-with-us/benefits
URBN celebrates diversity and is committed to creating an inclusive environment for all employees. We are proud to provide equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, sex (including gender, pregnancy, sexual orientation, and gender identity or expression), religion, creed, age, physical or mental disability, national origin or ancestry, ethnicity, citizenship, service in the uniformed services, genetic information, or any other protected characteristic as established by law. We believe strongly in fostering a safe, fair and respectful work environment. To ensure compliance with our non-discrimination and anti-harassment policies, we offer anti-harassment training to managers and employees.