About this role
Ready to make a serious impact? Millions of people already rely on Calendly, and we’re still in the midst of exciting product growth — it’s a fantastic time to join us. Everything you’ll work on here will accelerate your career to the next level. If you want to learn, grow, and do the best work of your life alongside the best people you’ve ever worked with, then we hope you’ll consider allowing Calendly to be a part of your professional journey. About the team & opportunity: What’s so great about working on Calendly’s Data Science & Machine Learning team? We make things possible for our customers through innovation in data, analytics and AI. Why do we need you? Well, we are looking for a Machine Learning Engineer who will deliver business value by executing the full machine learning lifecycle hands-on, from problem discovery through model deployment and monitoring. You will report to the head of Data Science & Machine Learning and will be responsible for building and operating ML-powered features that create magical experiences for our customers. Our team drives business insights, strategic decision making, executive level and cross organizational business growth, and magical customer experiences for our end customers through impactful innovation. Works closely with product, design, marketing, customer success, and engineering teams to implement ML models that improve the customer journey in service to growth and efficiency. Has a strong product focus and passion for using machine learning to solve real world problems, and understands that being an effective MLE is about collaborating with people as much as it is about writing code. You will join a high performing AI team and be an integral part of building new, machine learning based experiences for internal and external customers alike. Responsibilities include owning ML powered features from design through deployment, partnering with product, design, and engineering to scope work and define success metrics, understanding and sharing domain knowledge, prioritizing work independently, and serving as a subject matter expert for the features and services you own. Requirements include 4+ years of industry experience in applied Machine Learning or closely related fields, deep ability to traverse the full spectrum of ML life cycle, hands-on experience implementing ML models using a managed service, strong programming and data engineering skills, proficiency in ML frameworks such as Keras, Tensorflow, and PyTorch, experience working with time series data, and strong verbal and written communication skills. Authorized to work lawfully in the United States of America as Calendly does not engage in immigration sponsorship at this time.