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Spotify is looking for a Machine Learning Engineering Manager to join Native Ads team 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 an integral 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 Personalization and Amplify.
As the Machine Engineering Manager for the Optimyst Squad, you will solve complex problems surrounding forecasting campaign budgets, targeting optimization, and observability into campaign delivery systems with the goal to improve overall supply and campaign performance. Develop solutions to provide engaging music experiences for 350+ million active users using user behaviors and contextual information on 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 team to enhance current Native Ads product performance by experimenting with current and new ML models
- Participate in and challenge your team's systems architecture and modeling approaches, making the appropriate trade-offs based on metrics, quality, performance and cost, aligned with the team’s tech strategy
- Grow the technical expertise of your team through technical leadership and advocating for sound practices
- Identify, advocate for, and lead critical initiatives to advance technical and product performance in Native Ads
- Manage a team of ML, DE, BE and Web engineers to develop, maintain, and own business-critical models that serve the Music Promotion business
- Collaborate with a multi-functional, agile team, spanning user research, design, data science, product management, and engineering to build new product features that advance our mission
- Foster a healthy, collaborative and productive engineering team in line with our values
- Develop the team’s resilience amid fast change and ambiguity, supporting the team in building confidence in products and tech through prototyping and experimentation
- Grow people and the team through hiring, coaching, mentoring, feedback, process and continuous improvement efforts
Who You Are
- You have a strong background in statistics/ML/AI technologies and their application to consumer products
- You are invested in balancing developing thriving engineers and helping teams achieve significant business impact
- You thrive in ambiguity, balancing tech health with speed of impact and learning, and are able to help a team incorporate new information as it emerges
- Your strong product intuition allows you to efficiently connect the dots between multiple systems at Spotify
- You have experience or a strong interest in emerging agent technologies and generative recommender systems
- You aim to build capabilities tha deliver a great, safe, and trusted experience to our customers and Spotify users
- You understand the challenges of deploying and monitoring models in production, and can translate product metrics into model improvement strategies
- A plus if you have some knowledge of Ads systems
Who You Are
- This role is based in New York
- We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.
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.
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.
Spotify New York, New York, USA Office
4 World Trade Center, New York, NY, United States, 10007
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
