Company
Music
MachineLearningEngineer-Artist-FirstAIMusicLab
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Machine Learning Engineer - Artist-First AI Music Lab. Skills: Machine learning, Generative AI, LLM, Prompt engineering. Design machine learning training pipelines. Build machine learning training pipelines”
What You'll Achieve.
Take features to production; Improve model quality
Industry & Context.
Data-driven decisions
What They're Looking For.
Must Have
Experience applying machine learning in production, Hands-on experience with large language models, Experience building and maintaining production ML systems, Experience building large-scale data pipelines, Worked with cloud platforms, Explaining machine learning concepts, Experience building user-facing products, Experience with conversational AI, Experience with generative user experiences, Experience using data to guide decisions
Nice to Have
Prompt engineering experience, LLM-driven features in production, GCP, AWS, Azure experience, Judgment around conversational AI, Judgment around generative user experiences
What You'll Do.
Design machine learning training pipelines
Build machine learning training pipelines
Evaluate machine learning training pipelines
Improve machine learning training pipelines
Design inference pipelines
Build inference pipelines
Evaluate inference pipelines
Improve inference pipelines
Apply machine learning
Apply prompt engineering
Create evaluation frameworks
Build fast feedback loops
Partner with subject-matter experts
Bootstrap training data
Bootstrap reference data
Build scalable systems
Balance experimentation velocity
Balance production rigor
Collaborate with Data Science teams
Connect evaluation frameworks
Improve model quality
Contribute to technical direction
Contribute to engineering best practices
Work cross-functionally with engineering
Work cross-functionally with product
Work cross-functionally with design
Work cross-functionally with music industry partners
Shape listening experiences
How You'll Work.
Team & Collaboration
Cross-functional teams; Cross-functional agile teams; Cross-functional product teams; Cross-functional design teams; Cross-functional music industry partners
Communication Scope
Explaining concepts; Explaining assumptions; Explaining trade-offs
Process & Methodology
Experimentation, Iteration
Full Job Description
## Description The Music Mission team owns Spotify’s end to end proposition for music creators and the experiences they create for fans. The team is dedicated to building tools and services to enable creation, promotion, expression, and monetization at scale. Our Artist-First AI Music Lab designs and builds state-of-the-art generative AI products for music that create breakthrough experiences for fans and artists. We are currently searching for a Machine Learning Engineer to join our journey as we invent entirely new listening experiences that center and celebrate artists and creatives. All of our products put artists and songwriters first through four guiding principles: Partnerships with record labels, distributors, and music publishers: We’ll develop new products for artists and fans through upfront agreements, not by asking for forgiveness later. Choice in participation: We recognize there’s a wide range of views on use of generative music tools within the artistic community. Therefore, artists and rightsholders will choose if and how to participate to ensure the use of AI tools aligns with the values of the people behind the music. Fair compensation and new revenue: We will build products that create wholly new revenue streams for rightsholders, artists, and songwriters, ensuring they are properly compensated for uses of their work and transparently credited for their contributions. Artist-fan connection: AI tools we develop will not replace human artistry. They will give artists new ways to be creative and connect with fans. We will leverage our role as the place where more than 700 million people already come to listen to music every month to ensure that generative AI deepens artist-fan connections. ## What You’ll Do Design, build, evaluate, and improve machine learning training and inference pipelines that power new AI-driven music experiences and help take them to fully scaled production-ready features. Apply machine learning and prompt engineering knowledg
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