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About the Role

The Personalization team enhances music and podcast discovery for millions of users. The Surfaces Moments ML team focuses on creating moment-based experiences, including the Home Shortcuts feature, by leveraging machine learning and recommendation systems. As a Staff Machine Learning Engineer, you will drive the future of personalized discovery and engagement, working with recommendation systems, large language models, and production ML infrastructure to build impactful user experiences.

Responsibilities

Own and improve machine learning models and systems for the Home feed and Shortcuts experience.
Design, build, and ship personalized recommendations for millions of global users.
Build content recommendation systems for emerging agentic and AI-powered user experiences.
Train, fine-tune, evaluate, and optimize large language models using techniques like SFT, distillation, and parameter-efficient training.
Collaborate 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 for personalization at scale.
Drive technical direction in ambiguous problem spaces and contribute to long-term architecture.
Mentor and support other machine learning engineers.

Requirements

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 platforms.
Strong proficiency in Python and hands-on experience with PyTorch for building ML systems.
Experience with large language model training, fine-tuning, evaluation, and optimization techniques (SFT, distillation, LoRA).
Experience with large-scale inference systems, including latency, reliability, and cost optimization.
Ability to design, execute, and interpret online experiments and A/B tests.
Experience operating distributed ML workloads using technologies like Ray, FSDP, HSDP, or similar.
Experience building and maintaining data pipelines and orchestration workflows using technologies like Flyte, Airflow, BigQuery, and cloud storage.

Skills

Python
PyTorch
Recommendation Systems
Large Language Models (LLMs)
Machine Learning
A/B Testing
Data Pipelines
Ray
FSDP
HSDP
Flyte
Airflow
BigQuery

Location

North Americas region

Work Type

Remote

Experience Level

8+ years

Salary/Compensations

$227,495 - $324,993 plus equity

Benefits

Health insurance
Six month paid parental leave
401(k) retirement plan
Monthly meal allowance
23 paid days off
13 paid flexible holidays
Paid sick leave

About the Company

Spotify is an equal opportunity employer.
Our platform is for everyone, and so is our workplace.
We are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone.
We have ways to request reasonable accommodations during the interview process.

Equal Opportunity

Spotify is an equal opportunity employer.
You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones.
Our platform is for everyone, and so is our workplace.
The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking!
So bring us your personal experience, your perspectives, and your background.
It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
We are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone.
We have ways to request reasonable accommodations during the interview process and help assist in what you need.
If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.