Senior Machine Learning Engineer, Surfaces Moments

Spotify; New York (NY); Hybrid; USD 184,050 - 262,928; Full time

Benefits offered by this job

Health insurance

Six month paid parental leave

401(k) retirement plan

Monthly meal allowance

23 paid days off

Job summary

Spotify is seeking a Senior Machine Learning Engineer in the Personalization group to advance the Home feed and Shortcuts experiences with cutting-edge ML models. You will design and deploy scalable recommendation systems, with emphasis on production-ready ML infrastructure and robust experimentation at global scale.

You will collaborate across product, engineering, data science, and design teams, focusing on latency, reliability, and cost efficiency while advancing AI-powered content

Qualifications

• 5+ years of experience building and deploying ML systems in production environments.
• Deep expertise in recommendation systems, ranking models, personalization, or large-scale content discovery.
• Strong proficiency in Python and hands-on experience with PyTorch.
• Experience with large language model training, fine-tuning, evaluation, and optimization (SFT, distillation, LoRA).
• Experience with large-scale inference systems addressing latency, reliability, and cost.

Responsibilities

• Own and improve ML models and systems powering the Home feed and Shortcuts experiences.
• Design, build, and ship personalized recommendations for millions of Spotify listeners.
• Build content recommendation systems for AI-powered user experiences.
• Train, fine-tune, evaluate, and optimize large language models (SFT, distillation, LoRA).
• Collaborate with product, eng, data scientists, and designers to run experiments.
• Drive A/B testing, monitoring, and continuous optimization of recommendation quality, reliability, and cost.
• Improve ML platform capabilities, data pipelines, and production systems at Spotify scale.

Skills

Python

PyTorch

Recommendation systems

Large language models

A/B testing

Distributed systems

Data pipelines

Ray

Online experimentation

Cloud platforms

Tools

PyTorch

Ray

Flyte

Airflow

BigQuery

Cloud storage

Job 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 Senior 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, collaborating across disciplines, 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.
  
  

Who You Are

• You have 5+ 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 enjoy working in highly collaborative environments.
• 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.
  
  

The United States base range for this position is $184,050 $262,928 plus equity. 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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice

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