Staff ML Engineer: Personalization & Discovery

Remote; San Francisco (CA); Hybrid; USD 260,000 - 360,000; Full time

Job summary

Spotify is seeking a Staff Machine Learning Engineer for the Personalization organization. You will shape future personalized discovery and engagement by advancing recommendations, LLMs, and scalable ML infrastructure.

You will collaborate with product, research, and engineering teams to deploy models from research to production, optimize latency and cost, and mentor teammates across the ML平台.

Qualifications

• 8+ years of experience building and deploying machine learning systems in production.
• Deep expertise in recommendation systems, ranking models, personalization, or large-scale content discovery.
• 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 operating distributed ML 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.
• Ability to design, execute, and interpret online experiments and A/B tests to improve user outcomes.
• You communicate effectively across technical and non-technical audiences and influence technical decisions beyond your team.

Responsibilities

• Own and improve the machine learning models and systems powering the Home feed and Shortcuts experience.
• Design, build, and ship personalized recommendations serving millions of Spotify listeners globally.
• Build content recommendation systems for agentic and AI-powered experiences.
• Train, fine-tune, evaluate, and optimize large language models (SFT, distillation, LoRA).
• Partner with product, engineering, data science, and design to define experimentation strategies.
• Drive A/B testing, monitoring, model evaluation, and continuous optimization of recommendation quality and cost.
• Improve ML platform capabilities, data pipelines, and production systems for personalization at scale.
• Provide technical direction and mentor other ML engineers.

Skills

Python

PyTorch

Recommendation systems

Experimentation

Online experiments

A/B testing

Tools

Ray

Flyte

Airflow

BigQuery

Job description

Spotify is seeking a Staff Machine Learning Engineer for the Personalization organization. You will shape future personalized discovery and engagement by advancing recommendations, LLMs, and scalable ML infrastructure.

You will collaborate with product, research, and engineering teams to deploy models from research to production, optimize latency and cost, and mentor teammates across the ML平台.