Machine Learning Engineer, Content and CatalogManagement

The Catalog and Content Management (CoCaM) team worksat the heart of the Content Platform R&D studio, the centralpoint for the ingestion, distribution, management, knowledge andgrowth of all content you experience through Spotify products. InCoCaM we drive the management of content and make decisions thatimpact the whole of Spotify on all content’s appropriateness,availability, quality and accuracy. Through reactive and proactivereporting mechanisms we use the knowledge of Content Platform andapply platform & business policy with content, user, financialand experiential context to make and store a decision best forCreators, Consumers and Spotify. Location: - London Job type:Permanent This is an outstanding opportunity to contribute to thedevelopment and application of ML within our content and cataloguemanagement platform. You’ll be at the forefront of drivingimpactful solutions, while collaborating within a dynamic andsupportive team environment. What You'll Do: - Drive the fulllifecycle of ML solutions for CoCaM services, including research,design, development, evaluation, and deployment. - Manage MachineLearning projects ranging from Supervised Learning, toReinforcement Learning, to LLMs. - Optimize and monitor deployed MLmodel performance, implementing improvements based on analysis. -Document and standardize ML processes, pipelines, and modelspecifications. - Collaborate with cross-functional teams spanningresearch, engineering, data science, product managers and otherstakeholders to understand business needs and identifyopportunities for ML applications. - Work closely with engineeringteams to integrate ML models into existing systems and workflows. -Be an active participant of a group of machine learning engineers,staying updated with the latest advancements, participating in codereviews, and contributing to knowledge sharing across the team. WhoYou Are: - 2+ years of hands-on experience in developing anddeploying machine learning models in a production environment. -Practical experience in implementing ML systems using languageslike Python or Scala and are familiar with relevant ML librariesand frameworks (e.g., TensorFlow or PyTorch). - Solid understandingof various machine learning algorithms (e.g., classification,regression, clustering) and their practical applications. -Proficient in data manipulation and analysis using tools like SQLand Pandas. - Broad ML skillset and are happy to work on allaspects of ML problems. Not only modeling, but also feature work indata pipelines, some implementation in data pipeline workflows,experimentation setup and analysis. - Experience with modelevaluation metrics and techniques for ensuring model quality andgeneralization. - Experience with cloud platforms (e.g., GCP, AWS,Azure) and their ML services. - Comfortable communicating technicalconcepts clearly and effectively within the team and withnon-technical stakeholders. - Proactive problem-solver with astrong sense of ownership and a drive to learn. Where You'll Be: -This role is based in London (UK) - We offer you the flexibility towork where you work best! There will be some in-person meetings,but still allows for flexibility to work from home. Extensivelearning opportunities, through our dedicated team, GreenHouse.Flexible share incentives letting you choose how you share in oursuccess. Global parental leave, six months off - fully paid - forall new parents. All The Feels, our employee assistance program andself-care hub. Flexible public holidays, swap days off according toyour values and beliefs. Learn about life at Spotify. You arewelcome at Spotify for who you are, no matter where you come from,what you look like, or what’s playing in your headphones. Ourplatform is for everyone, and so is our workplace. The more voiceswe have represented and amplified in our business, the more we willall thrive, contribute, and be forward-thinking! So bring us yourpersonal experience, your perspectives, and your background. It’sin our differences that we will find the power to keeprevolutionizing the way the world listens. Spotify transformedmusic listening forever when we launched in 2008. Our mission is tounlock the potential of human creativity by giving a millioncreative artists the opportunity to live off their art and billionsof fans the chance to enjoy and be passionate about these creators.Everything we do is driven by our love for music and podcasting.Today, we are the world’s most popular audio streaming subscriptionservice with a community of more than 500 million users.#J-18808-Ljbffr