Senior Machine Learning Engineer, Personalization

What You'll Do

• Design, build, evaluate, and ship ML solutions for safety in Spotify’s personalization products
• Collaborate with cross functional teams spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and useful ways
• Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users
• Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization
• Be part of an active group of machine learning practitioners in New York (and across Spotify) collaborating with one another

Who You Are

• An experienced ML practitioner motivated to work on complex real-world problems in a fast-paced and collaborative environment -
• Strong background in machine learning, natural language processing, and generative AI, with experience in applying theory to develop real-world applications
• Hands-on expertise with implementing end-to-end production ML systems at scale in Java, Scala, Python, or similar languages. Experience with Pytorch, TensorFlow, Scikit-learn etc is a strong plus
• Experience with designing end-to-end tech specs and modular architectures for ML frameworks in complex problem spaces in collaboration with product teams
• Experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, and cloud platforms like GCP or AWS

Where You'll Be

• We are a distributed workforce enabling our band members to find a work mode that is best for them!
• Where in the world? For this role, it can be within the Americas region in which we have a work location
• Prefer an office to work from home instead? Not a problem! We have plenty of options for your working preferences. Find more information about our Work From Anywhere options here.
• Working hours? We operate within the Eastern Standard time zone for collaboration