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Staff Machine Learning Engineer for Content and Catalog Management
1 month ago
We're on a mission to enrich the lives of millions of users worldwide by bringing the music and audio they love to their devices, apps, and platforms. As a key member of the Experience team, you'll play a crucial role in shaping the future of Spotify's content and catalog management.
About the RoleWe're seeking a seasoned Machine Learning (ML) Staff Engineer to drive the adoption and expansion of ML usage within our content and catalog management platform. You'll work closely with a community of engineers, researchers, product managers, designers, and data scientists to own the expansion of CoCaM ML knowledge and expertise.
Key Responsibilities- Develop and implement ML strategies for content and catalog management across six squads, ensuring the platform supports diverse content types, policies, and provides data for reporting and auditability.
- Enhance the ML competence among 40+ engineers, engineering managers, and product managers, providing mentorship on the usage of ML with traditional engineering approaches.
- Partner with Staff Engineers and Product partners to identify and demonstrate ML opportunities, encouraging critical thinking within teams to develop a deeper understanding of ML.
- Cultivate strong relationships within the CoCaM team, promoting a culture of collaboration, openness, and inclusion to develop well-rounded solutions.
- Drive technical decisions and standard methodologies in ML to ensure high-quality and scalable solutions are built by our engineers.
- Stay updated with the latest ML advancements and Spotify ML standards, developing a learning environment to continuously improve the team's skills and knowledge.
- A proven track record of creating, promoting, and growing ML strategy for platforms, delivering horizontal solutions to vertical problems.
- Hands-on experience in implementing ML systems at scale in Java, Scala, Python, or similar, as well as with ML-specific libraries and frameworks like TensorFlow, PyTorch, or similar.
- In-depth knowledge of various ML algorithms, including supervised, unsupervised, and reinforcement learning, with experience in algorithm selection, tuning, and evaluation.
- Deep experience communicating sophisticated ML practices, solutions, and algorithms to technical and non-technical parties, with a focus on education and knowledge sharing.
- Experience leading ML projects, mentoring more inexperienced engineers, and driving technical strategy and decision-making within teams.
- Experience with containerization and orchestration tools like Docker and Kubernetes, as well as cloud platforms such as GCP, AWS, or Microsoft Azure, and familiarity with cloud-based ML services and tools.
- Comfortable writing queries, exploring data, and collaborating on hypotheses with product and engineering counterparts.
- Knowledge of model deployment techniques and serving frameworks like TensorFlow Serving, TorchServe, or custom APIs.
We're a distributed workforce, enabling our team members to find a work mode that suits them best. While we support candidates anywhere in EMEA, we have a preference for candidates in Stockholm, London, or Dublin, where many of our CoCaM team members are located. We also offer flexible work-from-home options, so you can choose the best environment for your productivity and well-being.
