Director of ML Engineering, Conversation Product Area

About the role

Spotify is looking for a Director of ML Engineering to take charge of the machine learning function within the Conversation Product Area. This leadership position involves guiding a team of engineers who build and maintain the systems that power conversational features on the Spotify platform. The Director is responsible for setting the technical vision, managing engineering resources, and ensuring that machine learning work delivers meaningful value to users. This role works closely with product and data science counterparts to define how ML capabilities are integrated into Spotify's conversation-related offerings. The Director also plays a strategic role in determining which ML investments will have the greatest long-term impact on the product area's goals and overall user experience. The Director reports to senior engineering leadership and is a key voice in shaping Spotify's broader ML strategy.

Key facts

What you'll do

• Lead the ML engineering team that operates within the Conversation Product Area at Spotify
• Define and drive the technical roadmap for machine learning systems powering conversation features
• Partner with product managers and stakeholders to identify opportunities where ML can create value
• Oversee the full lifecycle of ML model development from experimentation through production deployment
• Provide technical mentorship and career guidance to engineers at all levels on the team
• Create and enforce standards for model training procedures, evaluation metrics, and production monitoring
• Coordinate with data science teams to ensure smooth translation of research into engineering deliverables
• Allocate resources, set priorities, and manage project timelines across multiple ML initiatives simultaneously
• Establish reliability and performance benchmarks that ML-powered conversation features must meet in production
• Participate in architecture reviews and represent the Conversation Product Area in cross-team technical forums
• Stay current with developments in machine learning research and assess relevance to Spotify's product needs
• Foster a team culture centered on data-driven decision-making, accountability, and iterative improvement
• Drive collaboration between the ML engineering team and other engineering groups across Spotify to share knowledge and best practices
• Ensure that ML infrastructure and tooling are scalable and well-maintained for long-term growth

Requirements

• Substantial leadership experience directing engineering teams that build and ship machine learning systems
• Thorough knowledge of machine learning techniques and their practical application at scale
• Strong software engineering foundation with the ability to contribute to code and system design
• Demonstrated success leading ML initiatives within a product-driven organization that serves large user bases
• History of delivering ML-powered features that have measurable impact on user experience or business outcomes
• Skill in communicating complex technical concepts clearly to both engineering and non-engineering audiences
• Comfort operating in a dynamic environment where priorities shift and ambiguity is common
• A bachelor's degree in computer science, software engineering, or a closely related technical discipline
• Experience managing cross-functional projects that involve both engineering and non-engineering participants across multiple product areas

Nice to have

• Hands-on experience with conversational AI systems or natural language processing in a production setting
• Background in music streaming, audio technology, or recommendation systems relevant to the media domain
• Experience leading engineering teams that span multiple offices or operate across different geographic regions
• A history of contributing ML research through publications, talks, or presentations at industry events

Skills & tools

• Working proficiency in Python and SQL for building data pipelines and developing ML models
• Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or equivalent libraries
• Familiarity with major cloud computing platforms including AWS, GCP, or Azure for model serving and infrastructure
• Practical knowledge of containerization and orchestration technologies like Docker and Kubernetes for deployment
• Understanding of data processing and workflow tools such as Apache Airflow, Spark, or similar platforms
• Regular use of version control systems and continuous integration and delivery pipelines in daily work

Practical notes

• This position is located in New York, NY and is a full-time permanent role at Spotify
• The expected work arrangement is on-site or hybrid, following Spotify's current office policies for this location
• The interview process will include a series of technical conversations and leadership-focused evaluations
• Spotify welcomes applications from all qualified candidates and is committed to building a diverse and inclusive workforce
• Candidates should be prepared to discuss their leadership philosophy and approach to team management during interviews

About the company

Spotify is the world's most popular audio streaming subscription service with over 600 million users. Founded by Daniel Ek and Martin Lorentzon in 2006, Spotify went public via direct listing on the NYSE in April 2018. The platform hosts over 100 million tracks and 6 million podcasts.