Staff Machine Learning Engineer, Personalization

What You'll Do

• • 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.

  • Drive technical direction in ambiguous problem spaces and contribute to the long-term architecture of personalization systems.

  • Mentor and support other machine learning engineers, helping raise the bar across the team.

Who You Are

• • You have 8+ years of experience building and deploying machine learning systems in production environments.

  • You have deep expertise in recommendation systems, ranking models, personalization, or large-scale content discovery platforms.

  • You have strong proficiency in Python and hands-on experience building machine learning systems with PyTorch.

  • You are experienced with large language model training, fine-tuning, evaluation, and optimization techniques including SFT, distillation, and LoRA.

  • You have worked with large-scale inference systems and understand the challenges of latency, reliability, and cost optimization.

  • You care deeply about creating high-quality user experiences through thoughtful application of machine learning.

  • You communicate effectively across technical and non-technical audiences, and you influence technical decisions beyond your immediate team

  • You know how to design, execute, and interpret online experiments and A/B tests to improve user outcomes.

  • You have experience operating distributed machine learning workloads using technologies such as Ray, FSDP, HSDP, or similar frameworks.

  • You are experienced building and maintaining data pipelines and orchestration workflows using technologies such as Flyte, Airflow, BigQuery, and cloud-based storage platforms.

Where You'll Be

• • We offer you the flexibility to work where you work best! For this role, you can be within the North Americas region as long as we have a work location.

  • This team operates within the Eastern Standard time zone for collaboration.