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.

Location

New York

Job type

Permanent

As the Machine Engineering Manager for this team, 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.

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Our global benefits

Extensive learning opportunities, through our dedicated team, GreenHouse.

Flexible share incentives letting you choose how you share in our success.

Global parental leave, six months off - for all new parents.

All The Feels, our employee assistance program and self-care hub.

Flexible public holidays, swap days off according to your values and beliefs.

Learn about life at Spotify

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.