Staff Machine Learning Engineer, Ads Conversion Core Modeling
Leads technical direction for ads conversion machine learning, building low-latency, large-scale prediction models and using text, visual, and user signals to improve ad products.
We design Spotify's consumer experienceβend to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpointsβfrom our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.
You'll lead a senior-heavy group of 10β12 machine learning engineers, including Staff engineers, who team up dynamically to solve high-priority business problems while staying deep in content understanding (audio, video and text). This is a player-coach role with a strong strategic remit: you'll shape where the group goes next, grow our audio understanding expertise over the long term, and help the team scale through thoughtful, practical use of AI in everyday engineering work.
Leads technical direction for ads conversion machine learning, building low-latency, large-scale prediction models and using text, visual, and user signals to improve ad products.
Lead end-to-end development of production machine learning systems for cash-flow underwriting, shaping technical direction and turning transaction data into fair, accurate credit decisions and measurable member outcomes.
Lead hands-on development of the L2 driving model, diagnosing on-road issues and improving performance through data, model, evaluation, and release iterations while shaping a small technical team.
Leads technical delivery for machine learning systems, guiding engineering squads while contributing hands-on to architecture, prototypes, and complex engineering work across scalable, production-ready solutions.
Lead post-training and closed-loop development for Gaia, Wayveβs driving world model, improving long-horizon generation, model reliability, and downstream simulation impact through experimentation, data curation, and technical direction.