Senior Machine Learning Engineer, Personalization

Spotify; Boston (MA); Remote; USD 176,000 - 252,000; Full time

Job summary

Join a forward-thinking company as a Senior Machine Learning Engineer, where you will lead the development of innovative ML models for a new content engagement surface. This role offers the chance to work on exciting projects that enhance user experience across music, podcasts, and audiobooks. Collaborate with talented engineers in a dynamic environment, driving the future of machine learning strategies while enjoying the flexibility to work from anywhere in North America. If you are passionate about personalization and scalable ML systems, this opportunity is perfect for you.

Benefits

Health Insurance

Paid Parental Leave

401(k) Retirement Plan

Monthly Meal Allowance

Paid Time Off

Flexible Holidays

Paid Sick Leave

Qualifications

• Experience in machine learning, especially in recommender systems.
• Hands-on expertise with end-to-end production ML systems.

Responsibilities

• Architect and deploy Machine Learning models for real-time recommendations.
• Coordinate technical projects across teams and facilitate collaboration.

Skills

Machine Learning

Personalized Algorithms

Feature Engineering

Technical Leadership

Distributed Systems

Education

Bachelor's in Computer Science or related field

Master's in Machine Learning or related field

Tools

TensorFlow

Keras

Java

Scala

Python

Scio

spotify-kubeflow

Job description

The Now Playing View team is a new surface on Spotify that gives users a chance to engage deeply with the content they are currently playing, and explore new content related to what’s currently playing. With content like concerts, lyrics, and merchandise, as well as playable recommendations like music, podcasts, and audiobooks. There is a huge opportunity to scale and personalize recommendations on the surface.

The Home NPV team, which is taking ownership of this surface, is looking for a Senior Machine Learning Engineer to join a team of talented engineers that share a common interest in distributed systems, scalability and Machine Learning best practices. As one of the founding Machine Learning engineers on the team, you will be responsible for training and deploying the first models to power the NPV surface, across Music, Podcasts, and Audiobooks. You will work closely with the Backend and Data engineers on the team to ensure we meet latency requirements for serving the model on the request path as well as work closely with the Engineering Manager and Product Manager to drive the future of the Machine Learning strategy.

What You'll Do

• Coordinate technical projects across teams within Spotify
• Facilitate collaboration with other engineers, product owners, and designers to solve interesting and challenging problems for delivering various media worldwide
• Be a valued member of an autonomous, cross-functional agile team
• Architect, design, develop, and deploy the first Machine Learning models that will serve realtime recommendations across the Music, Podcast, and Audiobook NPV surfaces.
• Be a leader in personalization's Machine Learning community and work collaboratively and efficiently within Home’s existing platforms and systems.
• Hands-on expertise with implementing end-to-end production ML systems at scale in Java, Scala, Python, or similar languages
• Help drive optimization, testing, and tooling to improve quality

Who You Are

• You have experience being a technical leader or mentor
• You have a strong background in machine learning, with experience and expertise in personalized machine learning algorithms, especially recommender systems. (including experience in spotify-kubeflow and salem)
• You are experienced with feature engineering and building scalable data pipelines in Scio.
• You have a deep understanding of Machine Learning systems and infrastructure.
• You have experience in Tensorflow or Keras.

Where You'll Be

• We offer you the flexibility to work where you work best! For this role, you can be within the North America 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 $176,166 - $251,666 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, and paid sick leave. These ranges may be modified in the future.