Machine Learning Engineer, ML/AI

About The Company

Spotify is a global leader in music streaming and audio entertainment, renowned for its innovative approach to connecting creators and listeners worldwide. Since its inception in 2008, Spotify has transformed the way people access and enjoy music, podcasts, and other audio content. Our mission is to unlock the potential of human creativity by providing a platform that empowers over a billion users and a vast community of artists, podcasters, and content creators. We are committed to fostering an inclusive, diverse, and dynamic workplace where innovation thrives and everyone’s voice is valued. With a strong focus on technological excellence and user experience, Spotify continually pushes the boundaries of what’s possible in the digital audio space.

About The Role

We are seeking a skilled and motivated Machine Learning Platform Engineer to join our Hendrix ML Platform team in Toronto, Canada. In this role, you will be instrumental in developing and maintaining a scalable, reliable, and efficient platform for training and deploying machine learning models across Spotify. Your work will help streamline the productionization of AI and ML models, reducing complexity and enabling data scientists and engineers to focus on innovation. You will contribute to building tools, managing infrastructure, and collaborating with cross-functional teams including machine learning engineers, researchers, and product managers. This is a unique opportunity to influence the core platform that powers Spotify’s AI-driven features and services, ensuring they are scalable, robust, and aligned with industry best practices.

Qualifications

• 3+ years of hands-on experience in productionizing machine learning models
• Proficiency in deep learning frameworks such as PyTorch, TensorFlow, Hugging Face, or Ray
• Experience with distributed training leveraging GPUs and Kubernetes
• Strong understanding of data processing pipelines for machine learning
• Experience with cloud infrastructure and managing large-scale Kubernetes clusters
• Proficiency in programming languages such as Python, Scala, or similar
• Knowledge of agile software development methodologies
• Ability to design, document, and implement reliable and maintainable ML infrastructure solutions
• Excellent problem-solving skills and the ability to work independently and collaboratively

Responsibilities

• Contribute to the development and enhancement of the Spotify ML Platform SDK and related tools for ML operations
• Collaborate with machine learning engineers, researchers, and product teams to deliver scalable platform solutions
• Manage and maintain large-scale production Kubernetes clusters supporting ML workloads
• Design, implement, and document reliable, testable, and maintainable ML infrastructure components
• Support the deployment, monitoring, and optimization of ML models in production environments
• Stay current with emerging technologies and incorporate best practices into platform development
• Participate in code reviews, testing, and documentation to ensure high-quality deliverables
• Assist in troubleshooting and resolving infrastructure and deployment issues

Benefits

• Extensive learning opportunities through our dedicated GreenHouse team
• Flexible share incentives to participate in Spotify’s success
• Global parental leave policy offering six months off for all new parents
• Access to All The Feels employee assistance program and self-care resources
• Flexible public holidays, allowing you to swap days off based on personal values and beliefs
• Opportunities to work remotely with a flexible work environment
• Inclusive and diverse workplace culture that values personal perspectives and backgrounds

Equal Opportunity

Spotify is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We are dedicated to providing accessible recruitment processes and reasonable accommodations at every stage of the hiring process.