Staff Machine Learning Engineer, Home Surfaces

About the Position

Staff Machine Learning Engineer, Home Surfaces

New York, NY / Boston, MA

Engineering – Personalization

Permanent

Remote

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.

The Surfaces Podcasts team owns podcast recommendations across some of Spotify’s most visible surfaces, including Home and the Now Playing view. We build and improve the recommendation systems that help listeners discover their next favorite show or episode while helping creators reach the right audiences.

As a Staff Machine Learning Engineer, you’ll 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 for listeners at global scale. You’ll take models from research to production, help set technical direction in ambiguous problem spaces, and solve complex personalization challenges across Spotify.

Responsibilities

• 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 our personalization systems.
• Mentor and support other Machine Learning Engineers, sharing knowledge and helping strengthen engineering practices across the team.

Requirements

• Deep experience building and deploying machine learning systems in production environments.
• Deep experience with recommendation systems, ranking models, personalization, or large-scale content discovery platforms.
• 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 understanding the challenges of latency, reliability, and cost optimization.
• Commitment to creating high-quality user experiences through thoughtful applications of machine learning.
• Effective communication skills with technical and non-technical partners and the ability to influence technical decisions beyond your immediate team.
• Experience designing, executing, and interpreting 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.

We Offer

• The United States base salary range for this position is $227,495 - $324,993 plus equity.
• Benefits include health insurance, six months paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, and paid sick leave.

About the Company

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.

Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.

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: Spotify AI Notice