Who you are

• 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 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
• As a plus, you may have experience with adtech, categorization systems, and evaluation tools / data curation techniques

What the job involves

• 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
• 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
• 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

Benefits

• Extensive learning opportunities, through our dedicated team, GreenHouse
• Flexible share incentives letting you choose how you share in our success
• Global parental leave, six months off - fully paid - for all new parents
• All The Feels, our employee assistance program and self-care hub
• Flexible public holidays, swap days off according to your values and beliefs