Senior Principal Machine Learning Engineer - Recommendations

Sound Cloud empowers artists, tastemakers and fans to connect and share through music. Founded in 2007, Sound Cloud is a creator-first platform helping artists build and grow their careers by providing them with the most advanced tools, services, and resources.

With over 4x the music catalog of every other major streaming platform, spanning 40+ million artists across 190+ countries, Sound Cloud is where emerging artists find their sound, hidden gems are discovered, and music culture is shaped in real time.

Sound Cloud is seeking a Machine Learning leader to architect the next era of Musical Intelligence  a Senior Principal Engineer, you will combine deep technical expertise with strategic vision and people leadership to drive the development of large-scale recommendation, personalization, and search systems. The mission is clear: architect systems to extract high-fidelity insights from user interactions with the world’s largest audio dataset to connect artists and fans through music.

You will define the technical North Star for ML across engineering, delivering impactful data-driven products while leading and growing a high-performing team of Engineers and Scientists. This role reports directly to the Chief Technology Officer and will work in lockstep with the Music Intelligence, Content, and Recommendations teams. You will also be part of a small group leading the charge in architecting the agentic workflows and LLM-assisted systems that will allow us to ship Musical Intelligence at 10x the speed of traditional teams.

• Lead the technical strategy and execution for Sound Cloud’s ML systems (e.g., recommendation, ranking, personalization), including model development, deployment, and scaling
• Lead the exploration of advanced modeling techniques including Deep Neural Networks, LLMs, large recommender systems, multi-modal embeddings and transformer-based architectures to create unique and impactful listening experiences
• Define and drive the overall technical direction for ML in Sound Cloud including model architecture, feature engineering, training and serving infrastructure at scale, feature stores, pipeline orchestration, and model registry and versioning all aimed at accelerating our ability to bring ML-powered features to market
• Own short- and long-term objectives, ensuring ML investments deliver measurable user and business impact
• Lead, mentor, and grow ML Engineers and Scientists across Sound Cloud
• Be a strategic partner to the CTO in bringing an “ML Everywhere” strategy to all surfaces in the product (both Creator and Fan), and helping to lead the charge on AI-native engineering
• Stay current with industry trends and advancements in machine learning, identifying opportunities to apply them at Sound Cloud
• Lead the leveraging of agentic workflows and AI-assisted engineering as a force multiplier to work at 10x the speed of traditional methods

• 10+ years of experience in ML engineering, plus 3+ years in search or recommendations in an internet scale service with the reach of tens of millions of daily active users. Experience in a music streaming environment is a bonus
• Proven track record of defining technical strategy and driving execution for large-scale ML systems, particularly in recommendation, personalization, or search
• Experience setting technical roadmaps, influencing cross-functional priorities, and balancing business, product, and engineering trade-offs at an organizational level
• Experience leading and scaling teams of ML Engineers and Scientists, including hiring, mentoring, and developing high-performing talent
• Deep expertise in delivering data-driven products and ML solutions at scale on cloud-based platforms, with strong understanding of…