competitive salary
United Kingdom, Sweden
Information Technology, Engineering
English
in-office, remote, flexible
about the company
Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators.
diversity statement
"Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace."
your area of responsibility
Own the ML strategy for content and catalog management across six squads. Ensure the platform can support diverse content types, policies, provides data for reporting and auditability and enables the right balance of fast and accurate decisions
Enhance the ML competence among 40+ engineers, engineering managers and product managers. Provide mentorship on the usage of ML with traditional engineering approaches to use the right solution for the right problem
Partner with Staff Engineers and Product partners, policy owners and operational teams, to identify and demonstrate ML opportunities. Encourage critical thinking within teams to develop this understanding themselves
Cultivate strong relationships within the CoCaM Staff Engineers, Engineering Managers and Product Managers and promote the culture of collaboration, openness and inclusion to develop more well-rounded solutions
Promote experimentation and iteration to encourage more out-of-the-box approaches to engineering problems that we face and balance the need to deliver on the outcomes and goals we’re committed to
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 and develop a learning environment to continuously improve the team's skills and knowledge
your profile
You have a proven track record of creating, promoting and growing ML strategy for platforms and have used it to deliver horizontal solutions to vertical problems
You have hands-on experience in implementing ML systems at scale in Java, Scala, Python or similar and also with ML-specific libraries and frameworks like TensorFlow, PyTorch or similar
You have in-depth knowledge of various ML algorithms, including supervised, unsupervised, and reinforcement learning, and have experience with algorithm selection, tuning, and evaluation
You have deep experience communicating sophisticated ML practices, solutions and algorithms to technical and non-technical parties unfamiliar with ML terminology and principles. You see this educational opportunity as a key part of your role and always seek to help others understand and learn
You have shown experience in leading ML projects and mentoring more inexperienced engineers, and driving technical strategy and decision-making within teams
You have experience with containerization and orchestration tools like Docker and Kubernetes
You have experience with cloud platforms such as GCP, AWS, or Microsoft Azure, and familiarity with cloud-based ML services and tools, such as Google AI Platform, AWS SageMaker or Azure Machine Learning
You are comfortable writing queries, exploring data, and collaborating on hypotheses with product and engineering counterpart
You have knowledge of model deployment techniques and serving frameworks like TensorFlow Serving, TorchServe, or custom APIs
the 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.
