Leads engineering for Spotify’s Conversation Product Area, including shared agent infrastructure, evaluation systems, search, and voice platforms. The role manages approximately 70 engineers and requires deep technical leadership across large-scale ML platforms, agent systems, search, or speech infrastructure.
Staff ML Engineer on Spotify's Personalization team, owning ML models and systems for the Home feed and Shortcuts experience. Build and productionize personalized recommendation systems and agentic AI experiences using LLMs, PyTorch, and large-scale infrastructure; drive experimentation, optimization, and technical direction while mentoring engineers.
Senior ML Engineer on the Surfaces Moments team building personalized Home feed experiences and recommendation systems for Spotify listeners. Own models from research to production, fine-tune LLMs, drive A/B experiments, and optimize large-scale inference and data pipelines.
As a Senior Machine Learning Engineer, you will evolve large-scale ML pipelines and multimodal embedding frameworks to power Spotify's content-resolution systems. You will improve entity-resolution across music and video content, design experiments, and build scalable ML evaluation and monitoring infrastructure.
As a Staff Engineer, you will lead the design and evolution of data, backend, and ML infrastructure systems for Spotify's Content Intelligence Product Area. You will build scalable infrastructure for multimodal content processing and drive architectural decisions across distributed systems and AI-enabled platform capabilities.
Build and improve core agentic capabilities (memory, context, multi-step tool use) and evaluation frameworks (LLM-as-judge) for Spotify's Talk to Spotify conversational AI. Requires 5+ years production ML experience, rigorous evaluation skills, and comfort with rapid iteration on real user data.
Builds and scales ML systems for content moderation, policy enforcement, and safety scanning on Spotify. Develops multimodal models combining text, audio, image, video; architects feedback loops and evaluation frameworks for production-grade deployment.
Builds and scales ML systems for content understanding across audio, video, text, and images at Spotify. Develops models for classification, tagging, semantic analysis, and enrichment using LLMs, enabling automation, quality, and new product features.
Designs, builds, and deploys production ML systems for content safety, moderation, and policy enforcement at Spotify scale. Leads technical initiatives, develops multimodal/LLM models, and collaborates with Trust & Safety, Legal teams on safety-critical systems.
Designs and deploys LLM-based ML systems for personalized music recommendations, playlist generation, and session experiences at Spotify scale. Requires expertise in ML, NLP, generative AI, and large-scale data processing tools.
Senior ML Engineer on Spotify's Supply Personalization squad, designing and implementing ML systems to optimize ad loads, user behavior analysis, and ad experiences using causal inference and large-scale experimentation. Requires strong applied ML, software engineering, data analysis expertise, and proficiency in Python/Java/Scala, TensorFlow/PyTorch, and data pipelines.
Leads engineering for Spotify’s Conversation Product Area, including shared agent infrastructure, evaluation systems, search, and voice platforms. The role manages approximately 70 engineers and requires deep technical leadership across large-scale ML platforms, agent systems, search, or speech infrastructure.
Staff ML Engineer on Spotify's Personalization team, owning ML models and systems for the Home feed and Shortcuts experience. Build and productionize personalized recommendation systems and agentic AI experiences using LLMs, PyTorch, and large-scale infrastructure; drive experimentation, optimization, and technical direction while mentoring engineers.
Senior ML Engineer on the Surfaces Moments team building personalized Home feed experiences and recommendation systems for Spotify listeners. Own models from research to production, fine-tune LLMs, drive A/B experiments, and optimize large-scale inference and data pipelines.
As a Senior Machine Learning Engineer, you will evolve large-scale ML pipelines and multimodal embedding frameworks to power Spotify's content-resolution systems. You will improve entity-resolution across music and video content, design experiments, and build scalable ML evaluation and monitoring infrastructure.
As a Staff Engineer, you will lead the design and evolution of data, backend, and ML infrastructure systems for Spotify's Content Intelligence Product Area. You will build scalable infrastructure for multimodal content processing and drive architectural decisions across distributed systems and AI-enabled platform capabilities.
Build and improve core agentic capabilities (memory, context, multi-step tool use) and evaluation frameworks (LLM-as-judge) for Spotify's Talk to Spotify conversational AI. Requires 5+ years production ML experience, rigorous evaluation skills, and comfort with rapid iteration on real user data.
Builds and scales ML systems for content moderation, policy enforcement, and safety scanning on Spotify. Develops multimodal models combining text, audio, image, video; architects feedback loops and evaluation frameworks for production-grade deployment.
Builds and scales ML systems for content understanding across audio, video, text, and images at Spotify. Develops models for classification, tagging, semantic analysis, and enrichment using LLMs, enabling automation, quality, and new product features.
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Designs, builds, and deploys production ML systems for content safety, moderation, and policy enforcement at Spotify scale. Leads technical initiatives, develops multimodal/LLM models, and collaborates with Trust & Safety, Legal teams on safety-critical systems.
Designs and deploys LLM-based ML systems for personalized music recommendations, playlist generation, and session experiences at Spotify scale. Requires expertise in ML, NLP, generative AI, and large-scale data processing tools.
Senior ML Engineer on Spotify's Supply Personalization squad, designing and implementing ML systems to optimize ad loads, user behavior analysis, and ad experiences using causal inference and large-scale experimentation. Requires strong applied ML, software engineering, data analysis expertise, and proficiency in Python/Java/Scala, TensorFlow/PyTorch, and data pipelines.