Machine Learning Engineer II - Ad Forecasting

Spotify•New York, NY

16d•Remote

About The Position

Our mission on the Advertising Product & Technology team is to build a next generation advertising platform that aligns with our unique value proposition for audio and video. We work to scale the user experience for hundreds of millions of fans and hundreds of thousands of advertisers. This scale brings unique challenges as well as tremendous opportunities for our artists and creators. We are seeking a Machine Learning Engineer with expertise in machine learning model development, AI engineering, online experimentation techniques, and large-scale engineering systems. This role will lead strategic initiatives and projects within Ads Forecasting. The Ads Forecasting squad focuses on building and maintaining the models and systems that predict future ad inventory,demand, and performance across Spotify's platform. By leveraging data and experimentation, we aim to provide accurate, timely forecasts that drive key business decisions, optimize ad delivery, and ensure the long-term health of our advertising business. We operate on the cutting edge of both machine learning and AI engineering, employing both in-house first party models developed through traditional machine learning and state-of-the-art time-series and predictive modeling techniques. We are looking for someone who is motivated by user and business problems as much as they are by technical problems, and who enjoys ambiguity, brainstorming, experimentation, and iteration. You will work in close collaboration with key stakeholders across engineering, product, business, and leadership teams to build the most impactful solutions for our Spotify listeners and business partners.

Requirements

You have professional experience in applied machine learning
You have strong technical expertise in application development, microservice architecture, distributed systems and/or data analysis
You are proficient in programming languages such as Python, Java, or Scala
You are skilled with operating in a cloud-native infrastructure
You have experience in developing data pipelines using tools like Apache Beam or Spark

Nice To Haves

You may have experience with adtech, categorization systems, and evaluation tools / data curation techniques

Responsibilities

Design and implement machine learning systems to predict future ad inventory,demand, and performance
Research and apply best practices for driving automation with respect to human review processes
Partner with multiple teams to shape and enhance shared systems and pipelines
Come up with creative ways to apply AI tools to develop innovative solutions
Collaborate with and lead backend engineers, data scientists, data engineers, and product managers to establish baselines, inform product decisions, and develop new technologies