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Machine Learning Engineering Manager
Spotify
- Location
- United States of America
- Posted
- Salary Range
- 176k - 252k USD
Data-minded Engineering Manager with ML expertise to lead Ads Performance Platform - Demand team at Spotify
Spotify
Data-minded Engineering Manager with ML expertise to lead Ads Performance Platform - Demand team at Spotify
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We seek a data-minded Engineering Manager with machine learning expertise to lead a squad within the Ads Performance Platform - Demand product area at Spotify. The team will own relevance modeling, user ad embeddings, and probabilistic audiences to boost advertiser performance and listener relevance. This role requires collaboration with key stakeholders across engineering, product, business, and leadership teams to build impactful solutions for Spotify listeners and business. The ideal candidate is motivated by user and business problems, enjoys ambiguity, brainstorming, experimentation, and iteration. They should have experience in engineering management or technical leadership roles, software engineering, data analysis, and machine learning. Spotify offers flexible remote work options, a competitive salary range of $176,166- $251,666 plus equity, and comprehensive benefits.
Our mission on the Advertising Product & Technology team is to build a next generation advertising platform that aligns with our unique value proposition for audio and video. We work to scale the user experience for hundreds of millions of fans and hundreds of thousands of advertisers. This scale brings unique challenges as well as tremendous opportunities for our artists and creators.
We seek a data-minded Engineering Manager with machine learning expertise to lead a squad within the Ads Performance Platform - Demand product area. The squad will own relevance modeling, iterating on our user ad embeddings and extending that to all ad types. This team will also help support probabilistic audiences (interests, contextual, demo) that can build off of our understanding of user ad preferences to help advertisers reach the most relevant audiences, and expand those audiences in a way that boosts advertiser performance and listener relevance. They will work closely with our ad formats and data platform teams to create new signals of listener preferences and expand Spotify’s ad targeting capabilities with performant audience segments.
We are looking for someone who is as motivated by user and business problems as they are by technical problems, and who enjoys ambiguity, brainstorming, experimentation, and iteration. You will work in close collaboration with key stakeholders across engineering, product, business, and leadership teams to build the most impactful solutions for our Spotify listeners and business.
What You'll Do
Lead a team of talented engineers to develop and execute strategies for ad relevance to maximize ad performance and increase revenue.
Use data analysis and machine learning techniques to understand user behavior and opportunities to optimize ad experiences.
Foster a culture of experimentation, encouraging the team to brainstorm, test, and iterate on innovative ideas.
Navigate and thrive in an environment filled with ambiguity, making data-driven decisions to steer the team towards success.
Collaborate closely with Product counterparts to drive effective leadership, maximize impact and align our efforts with the broader group's goals.
Collaborate closely with data scientists to design and analyze experiments and facilitate data-driven development.
Provide mentorship and professional growth opportunities to team members, fostering an inclusive and high-performing team environment.
Who You Are
Experience in engineering management or technical leadership roles, with a focus on growth and ad technology. Experience in high-growth tech companies is a plus.
Strong background in software engineering, data analysis, and machine learning. Proficiency in programming languages such as C languages, Python, Java, or Scala.
Demonstrated ability to make decisions based on data and analytics. Comfort with SQL and data visualization tools. Comfort in business concepts such as Supply/Demand, OKRs, and Opportunity Sizing.
Proven track record of brainstorming and implementing experimental ideas to drive growth.
Exceptional leadership and team management skills, with experience guiding teams through ambiguity and change.
Excellent communication and collaboration skills, with the ability to work effectively across different teams and departments.
Bachelor’s or Master’s degree in Computer Science, Data Science, or a related quantitative field.
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, 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.
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.