Staff Machine Learning Engineer - NativeAds
Spotify is looking for a Staff ML Engineer to join the Native Ads product area in the Music Mission. In Native Ads, we build consumer and industry-facing music promotion products which provide creators new avenues for promoting their work, reaching new audiences, and deepening their connections with fans. You will play a crucial role in shaping the future of Native Ads products, technology and business, and represent Native Ads in the continuously evolving Coordinated Promotions ecosystem by collaborating with key partners in PZN and Ads.
As the Staff Machine Learning Engineer for this team, you will work with a cross-functional team to define and execute a Machine Learning technical strategy for the product area. Working with a team of Engineering Managers, Staff and Senior Staff Engineers, along with a team of engineers and partners in PZN, you will shape and drive initiatives that tackle complex problems surrounding campaign forecasting, serving observability and targeting optimization with the goal to improve overall supply and campaign performance.
You will build ML-driven solutions to bring promotional music experiences to our 350+ million active users on behalf of millions of artists, using a diverse range of datasets including user behaviors, contextual data, and other signals across our broad range of mobile and connected platforms. Above all, your work will impact the way the world experiences music and the way creators connect to their fans!
What You'll Do
Lead the creation of a Machine Learning Engineering Strategy for Native Ads
Contribute to designing, building, evaluating, shipping, and refining Native Ads products via hands-on ML development
Collaborate with a cross functional agile team spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans.
Prototype new approaches and productionize solutions for Spotify For Artists customers
Help drive optimization, testing, and tooling to improve quality.
Work closely with Personalization and Music Tech Research teams to ideate and innovate on Music Promotion Tools
Who You Are
You have a strong background in machine learning, with experience and expertise in machine learning algorithms.
You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages.
You have experience or a strong interest in emerging agent technologies and generative recommender systems
You care about agile software processes, data-driven development, reliability, and disciplined experimentation
You enjoy leading projects from start to finish working closely with your team and peers. You are comfortable dealing with ambiguity on high impact projects
Be accountable to senior tech leadership for meeting our product and technology objectives and managing expectations if those are at risk
Passion for the opportunity to better serve artists & their teams
Team-first approach with developed techniques to ensure teams are happy, motivated, and productive
A plus if you have experience with Ads systems
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 $215,136- $307,337 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.
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.
About the job
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Staff Machine Learning Engineer - NativeAds
Spotify is looking for a Staff ML Engineer to join the Native Ads product area in the Music Mission. In Native Ads, we build consumer and industry-facing music promotion products which provide creators new avenues for promoting their work, reaching new audiences, and deepening their connections with fans. You will play a crucial role in shaping the future of Native Ads products, technology and business, and represent Native Ads in the continuously evolving Coordinated Promotions ecosystem by collaborating with key partners in PZN and Ads.
As the Staff Machine Learning Engineer for this team, you will work with a cross-functional team to define and execute a Machine Learning technical strategy for the product area. Working with a team of Engineering Managers, Staff and Senior Staff Engineers, along with a team of engineers and partners in PZN, you will shape and drive initiatives that tackle complex problems surrounding campaign forecasting, serving observability and targeting optimization with the goal to improve overall supply and campaign performance.
You will build ML-driven solutions to bring promotional music experiences to our 350+ million active users on behalf of millions of artists, using a diverse range of datasets including user behaviors, contextual data, and other signals across our broad range of mobile and connected platforms. Above all, your work will impact the way the world experiences music and the way creators connect to their fans!
What You'll Do
Lead the creation of a Machine Learning Engineering Strategy for Native Ads
Contribute to designing, building, evaluating, shipping, and refining Native Ads products via hands-on ML development
Collaborate with a cross functional agile team spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans.
Prototype new approaches and productionize solutions for Spotify For Artists customers
Help drive optimization, testing, and tooling to improve quality.
Work closely with Personalization and Music Tech Research teams to ideate and innovate on Music Promotion Tools
Who You Are
You have a strong background in machine learning, with experience and expertise in machine learning algorithms.
You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages.
You have experience or a strong interest in emerging agent technologies and generative recommender systems
You care about agile software processes, data-driven development, reliability, and disciplined experimentation
You enjoy leading projects from start to finish working closely with your team and peers. You are comfortable dealing with ambiguity on high impact projects
Be accountable to senior tech leadership for meeting our product and technology objectives and managing expectations if those are at risk
Passion for the opportunity to better serve artists & their teams
Team-first approach with developed techniques to ensure teams are happy, motivated, and productive
A plus if you have experience with Ads systems
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 $215,136- $307,337 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.
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.