Staff Machine Learning Engineer, Personalization

2 months, 3 weeks ago
Full-time
Lead
Software Development
Spotify

Spotify

Spotify is a leading global audio streaming service empowering artists and inspiring fans worldwide with over 70 million tracks. It has 365 million users, including 165 million subscribers, across 178 markets.

Media
Founded 2006

Description

  • Own and improve the machine learning models and systems that power the Home feed, including the Shortcuts experience.
  • Design, build, and ship personalized recommendations for 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 methods such as supervised fine-tuning, distillation, and parameter-efficient training.
  • Partner 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 to raise the team’s overall bar.

Requirements

  • 8+ 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.
  • Experience with large-scale inference systems and an understanding of latency, reliability, and cost optimization.
  • Ability 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.
  • Strong communication skills across technical and non-technical audiences, with influence beyond the immediate team.
  • North America work location required, with collaboration in Eastern Standard Time.

Benefits

  • Base salary range of $227,495 to $324,993 in the United States.
  • Equity in addition to base compensation.
  • Health insurance.
  • Six months of paid parental leave.
  • 401(k) retirement plan.
  • Monthly meal allowance.
  • 23 paid days off.
  • 13 paid flexible holidays plus paid sick leave.
  • Flexible work location within North America, with remote flexibility where available.

Interested in this position?

Apply directly on the company website

Apply Now

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