Staff Machine Learning Engineer, Content and Catalog Management

What You'll Do

• 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

Who You Are

• 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

Where You'll Be

• We are a distributed workforce enabling our band members to find a work mode that is best for them! For the right candidate anywhere we support in EMEA is possible however we have a preference for a candidate in Stockholm, London or Dublin where many of CoCaM members are located
• 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 Work From Anywhere options here