Senior Machine Learning Engineer, Surfaces Moments

Spotify is a leading music streaming platform, and they are seeking a Senior Machine Learning Engineer to join their Personalization team. This role involves shaping the future of personalized discovery and engagement by working on recommendation systems and machine learning infrastructure to enhance user experiences.

Responsibilities:

• 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

Requirements:

• 5+ years of experience building and deploying machine learning systems in production environments
• Deep expertise in recommendation systems, ranking models, personalization, or large-scale content discovery platforms
• Strong proficiency in Python and hands-on experience building machine learning systems with PyTorch
• Experience with large language model training, fine-tuning, evaluation, and optimization techniques including SFT, distillation, and LoRA
• Worked with large-scale inference systems and understand the challenges of latency, reliability, and cost optimization
• Care deeply about creating high-quality user experiences through thoughtful application of machine learning
• Communicate effectively across technical and non-technical audiences and enjoy working in highly collaborative environments
• Know how to design, execute, and interpret online experiments and A/B tests to improve user outcomes
• Experience operating distributed machine learning workloads using technologies such as Ray, FSDP, HSDP, or similar frameworks
• Experience building and maintaining data pipelines and orchestration workflows using technologies such as Flyte, Airflow, BigQuery, and cloud-based storage platforms