Spotify

• Own and improve the machine learning models and systems that power the Home feed, including the Shortcuts experience. • Design, build, and ship personalized recommendations that serve millions of Spotify listeners globally. • Build content recommendation systems for emerging agentic and AI-powered user experiences. • Train, fine-tune, evaluate, and optimize large language models using techniques such as supervised fine-tuning (SFT), distillation, and parameter-efficient training approaches. • Partner closely with product managers, engineers, data scientists, and designers to define and execute experimentation strategies. • Drive A/B testing, monitoring, model evaluation, and continuous optimization of recommendation quality, reliability, and cost efficiency. • Improve ML platform capabilities, data pipelines, and production systems that support personalization at Spotify scale.

• Lead and develop a team of six experienced engineers • Accountability for team delivery • Partner with product and stakeholders for roadmap shaping • Drive technical strategy and architectural decisions • Build a culture of ownership, psychological safety, and continuous improvement • Collaborate across Data Platform and wider engineering organisation • Manage on-call health, operational excellence, and reliability • Participate in hiring and onboarding

• Define the long-term vision, strategy, roadmap, and execution for Habit Formation across Spotify's consumer experience. • Build the behavioral intelligence that helps identify when listeners are ready to discover new formats, features, or experiences. • Partner with engineering, machine learning, design, research, and data science to build experiences powered by behavioral insights and experimentation. • Translate advances in AI, recommendation models, and intelligent agents into intuitive consumer experiences that millions of listeners love. • Develop systems that encourage sustainable engagement while ensuring teams work together instead of competing for user attention. • Influence the evolution of Spotify's surfaces, information architecture, and product experiences to reinforce lasting listening habits. • Use experimentation, behavioral analysis, and user research to identify opportunities and make informed product decisions in ambiguous problem spaces. • Set clear product direction, make thoughtful prioritization decisions, and align senior leaders around a shared strategy. • Drive execution across multiple engineering teams while balancing quality, speed, user trust, and long-term business impact. • Establish Habit Formation as a strategic product capability that enables sustainable growth across Spotify.

• Define the product strategy and roadmap for a portfolio of User Platform products spanning account lifecycle management, IAM analytics, and device and client intelligence. • Partner closely with engineering managers, staff engineers, data scientists, analytics engineers, designers, researchers and insights teams to shape product direction and deliver long-term platform value. • Collaborate across missions, studios and product areas to ensure Spotify's identity and user data platform evolves to meet business and customer needs. • Help build Spotify's account lifecycle platform with well-defined account states, governed lifecycle transitions and comprehensive audit capabilities supporting Engineering, Customer Service, Legal and partner teams. • Lead the product vision for User Intelligence, the shared platform that enables trusted understanding of users, devices and sessions through reusable signals and APIs. • Partner with teams across User Fraud, Subscriptions, Advertising, Personalization, Safety, Legal and Platform to ensure trusted identity data becomes a strategic input for decision making. • Translate complex identity, trust and data challenges into clear product strategies, business outcomes and prioritization decisions. • Define success metrics including platform adoption, signal quality, data trust, lifecycle diagnosis time, decision latency and reduction of fragmented local solutions. • Balance long-term platform investments with near-term business priorities, regulatory requirements and user experience. • Foster an effective product operating rhythm across multiple squads by creating clarity, alignment and shared ownership that enables teams to move with confidence.

• Build, operate, and evolve scalable Scio data pipelines on Google Cloud Platform that process high-volume financial data with accuracy and reliability. • Develop and enhance Java backend services that power integrations across Spotify's financial ecosystem. • Design and evolve data models and datasets that support accounting, reconciliation, financial reporting, and operational insights. • Build and improve integrations with external financial systems to bring critical financial data into Spotify's financial ecosystem. • Partner closely with Finance, Product, and Engineering teams to translate accounting requirements into reliable, scalable technical solutions. • Improve the scalability, observability, and resilience of financial data pipelines and backend services. • Contribute to engineering best practices through continuous delivery, automated testing, monitoring, and thoughtful code reviews. • Help drive technical decisions that improve the long-term maintainability of Spotify's financial engineering platform.

• Be accountable for teams building Spotify Agentic Experience delivering new and innovative products at the heart of music, podcast and audiobooks users love. • Together with a wide range of collaborators, develop a generative AI tech strategy that keeps Spotify at the forefront of innovation in the field. • Provide servant leadership to several teams working across research, machine learning, engineering management, backend engineers, and data specialists. • Advocate for and increase knowledge of advanced Gen AI capabilities across the company, including influencing the company’s most senior leaders. • Cultivate a balanced, collaborative engineering culture and a diverse and inclusive team that reflects our customers and our world. • Directly manage ~5-10 people. • Collaborate with a product lead to define strategy, success metrics and roadmaps. • Influence the technical design and architecture of the Conversation team’s stack. • Influence the Personalization team’s research and roadmap. Collaborate with leaders throughout the company to plan and execute impactful initiatives requiring many teams.

• Be accountable for teams building Spotify Agentic Experience • Develop a generative AI tech strategy • Provide servant leadership to several teams • Advocate for and increase knowledge of advanced Gen AI capabilities • Cultivate a balanced engineering culture and a diverse team • Manage ~5-10 people • Collaborate with product lead to define strategy and success metrics • Influence the technical design and architecture of the Conversation team’s stack

• Lead the product strategy for BEAT and define the vision for agent-native backend development across Spotify's platform. • Shape how AI and LLM-powered capabilities transform the software development lifecycle, from coding and code review to deployment, observability, and incident response. • Stay close to the product by using and evaluating BEAT's developer tools, applying AI-augmented workflows, and leading high-impact product initiatives directly where needed. • Lead and develop a team of Product Managers, fostering a collaborative, high-performing team that operates with shared ownership and a consistently high product quality bar. • Partner closely with the Engineering Area Lead to align priorities, make investment decisions, and balance trade-offs across four engineering squads supporting approximately 40 engineers. • Build trusted partnerships with senior engineers and the Backend Advisory Board to ensure the roadmap reflects the evolving needs of Spotify's backend engineering community. • Collaborate across Product Areas, studios, and the broader Platform Mission to deliver shared infrastructure initiatives and drive alignment on strategic investments. • Own delivery against Core Infrastructure's strategic commitments, including AI-native product development lifecycle initiatives and continued adoption of the monorepo experience.

• Conduct groundbreaking research in generative audio using diffusion or flow matching models • Run large-scale experiments with access to Spotify's infrastructure and audience • Create practical applications harnessing generative technologies • Collaborate with a cross-functional team to craft innovative solutions • Engage with the broader research community by publishing findings and delivering talks

• Conduct groundbreaking research in generative audio using diffusion or flow matching models, with a focus on one or more of the following areas: • Vocal Synthesis — Research in vocal and speech synthesis, along with related areas such as ML-based audio processing and signal processing. • Post-Training — Research in post-training techniques for music generation, including preference alignment methods (such as DPO, RLHF, or KTO), reward model design and training, and reinforcement learning to improve output quality, controllability, and human preference adherence. • Editing — Research in iterative music generation and audio editing, including capabilities such as stem replacement, instrumentation change, mood changes (while preserving content), tempo changes, and structure changes. • Run large-scale experiments with access to Spotify's extensive infrastructure and an audience of more than 700 million monthly active users. • Create practical applications that harness generative technologies and push the boundaries of what's possible in listening experiences. • Collaborate as part of a cross-functional team—working closely with scientists, engineers, product managers, designers, user researchers, and analysts—to craft innovative solutions to complex challenges. • Have a direct impact on Spotify's products, tools, and services, working on projects that influence the entire organization. • Engage with the broader research community by publishing your findings, delivering talks, and attending top conferences.