Staff Machine Learning Engineer, Home Surfaces

Software; United States; À distance; USD 227 000 - 325 000; Plein temps

Avantages offerts par ce poste

Health insurance

Paid parental leave (6 months)

401(k) retirement plan

Monthly meal allowance

23 paid days off

13 paid flexible holidays

Paid sick leave

Résumé du poste

Spotify is seeking a Staff Machine Learning Engineer for the Home Surfaces team. You will shape personalized discovery, enhancing the Home feed and Shortcuts with ML-driven recommendations and large-language-model work at global scale.

You will collaborate with product, data scientists and engineers to run experiments, optimize latency and costs, and advance AI-powered user experiences across Spotify surfaces.

Qualifications

• Experience designing and deploying ML systems in production.
• Expertise in recommender systems, personalization, or large-scale discovery.
• Strong Python and PyTorch skills.
• Experience training/finetuning LLMs with SFT, distillation, LoRA.
• Experience with latency, reliability and cost optimization in inference.
• Able to communicate across technical and non-technical audiences.
• Proficient in online experimentation and A/B testing.
• Experience with distributed ML workloads and orchestration tools.

Responsabilités

• Own and improve ML models powering Home feed and Shortcuts.
• Design and ship personalized recommendations at scale.
• Build content recommendation systems for AI-powered experiences.
• Train/finetune LLMs using SFT, distillation, LoRA.
• Collaborate with product, engineers, data scientists and designers on experiments.
• Lead A/B testing, monitoring, evaluation, and optimization.
• Improve ML platform, data pipelines and production systems.
• Shape long-term personalization architecture and mentor others.

Connaissances

ML systems design

Recommendation systems

Online experiments

Python

PyTorch

Cross-team influence

Distributed ML

Data pipelines

Outils

Ray

FSDP

HSDP

LoRA

Flyte

Airflow

BigQuery

Cloud storage

Description du poste

Staff Machine Learning Engineer, Home Surfaces

Remote Unspecified Unspecified

Description

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we're behind some of Spotify's most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you'll keep millions of users listening by making great recommendations to each and every one of them.

Surfaces Moments is a ML team within the Personalization Mission focused on creating moment-based experiences across Spotify surfaces. The team owns and evolves the experiences that help listeners quickly connect with the content that matters most to them, including the Home Shortcuts experience and the underlying intelligence that powers it. By combining cutting-edge machine learning, recommendation systems, and product thinking, the team delivers highly relevant, personalized experiences to millions of listeners around the world.

As a Staff Machine Learning Engineer, you will help shape the future of personalized discovery and engagement at Spotify. You'll work at the intersection of recommendation systems, large language models, and production-scale machine learning infrastructure to build experiences that delight users and drive meaningful impact. This role is ideal for someone who enjoys taking models from research to production, driving technical direction in ambiguous problem spaces, and solving complex personalization challenges at global scale.

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 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.

Compensation

The United States base range for this position is $227,495- $324,993 plus equity.

Additional Information

• The benefits available for this position include 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.
• These ranges may be modified in the future.

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.

At Spotify, 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.