
67 open roles · Engineering
Staff Machine Learning Engineer - Music Mission
- Added to ZestAmigo
- Last seen on employer site
Where you can work
Remote
Eligibility not captured
Locations named in the listing
- New York City, New York, United States
- Boston, Massachusetts, United States
View location wording from the posting
- New York, NY
- Boston, MA
Employer 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.
The DISCO Product Area is focused on building promotional tools that help artists reach more fans. Our products serve artists at scale through Spotify for Artists, and we’re building on the momentum of Discovery Mode to help artists and their teams find new listeners when it matters most. As a Staff Machine Learning Engineer, you’ll help shape the Machine Learning technical strategy for this high-impact area, partnering across engineering, product, data science, research, and design to create tools that help artists grow their audiences while supporting Spotify’s core business.
What You'll Do
- Help define and drive the Machine Learning engineering strategy for Discovery Mode and related royalty programs, translating product goals into scalable technical solutions.
- Design, build, evaluate, ship, and refine production Machine Learning systems through hands-on development.
- Provide technical leadership across complex ML initiatives, helping teams make thoughtful architectural and engineering decisions while balancing near- and long-term priorities.
- Collaborate with user research, design, data science, product management, and engineering to build new product capabilities that strengthen connections between artists and fans.
- Prototype new approaches and turn successful ideas into reliable, scalable solutions for Spotify for Artists customers.
- Drive experimentation, optimization, testing, and tooling that improve the quality, reliability, and effectiveness of our Machine Learning systems.
- Partner with engineers and Machine Learning practitioners across Spotify, including Music Tech Research and Personalization, to explore and develop new approaches to music promotion.
- Help grow the technical capabilities of the broader engineering community through mentorship, knowledge sharing, and strong engineering practices.
Who You Are
- You have deep experience with Machine Learning and a strong understanding of Machine Learning algorithms, modeling approaches, evaluation, and experimentation.
- You have hands-on experience designing and implementing production Machine Learning systems at scale using languages such as Python, Java, Scala, or similar.
- You can set technical direction for complex ML problems while remaining close to implementation and delivery.
- You care about reliable software, data-informed development, disciplined experimentation, and building systems that perform effectively at scale.
- You enjoy leading technically complex projects from idea through production and working closely with teammates and partners to deliver meaningful outcomes.
- You are comfortable navigating ambiguity, evaluating trade-offs, and creating clarity on high-impact initiatives.
- You communicate technical decisions and risks clearly and can build alignment with senior technical leaders and cross-functional partners.
- You care about creating products that better serve artists and their teams, and you take a collaborative, team-first approach to helping others do their best work.
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 time zone for collaboration.
The United States base range for this position is $227,495.00 - $324,993 USD, 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, paid flexible holidays, and 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.
Track this application
Keep your own notes. Only you can mark an application as sent.
Report a problem with this listing
Sign in to report this listing.
More at Spotify
Hybrid
Stockholm, Stockholm, Sweden
Full-time
Salary unavailable
Posted 3 weeks ago
Source: Lever
On-site
New York City, New York, United States
Full-time · Manager
Salary unavailable
Posted 2 weeks ago
Source: Lever
Remote
Remote eligibility: Eligibility not captured
New York City, New York, United States
Full-time · Lead
Salary unavailable
Posted 1 month ago
Source: Lever
Remote
Remote eligibility: Eligibility not captured
New York City, New York, United States
Full-time · Lead
Salary unavailable
Posted 5 days ago
Source: Lever
Similar roles elsewhere
Remote
Remote eligibility: Eligibility not captured
Etobicoke, Ontario, Canada
Full-time
$250 to $250 CAD / hour
Posted 1 year ago
Source: Breezy HR
Remote
Remote eligibility: Eligibility not captured
Etobicoke, Ontario, Canada
Contract · Entry level
$32 to $32 CAD / hour
Posted 3 months ago
Source: Breezy HR
Unspecified
United States
Full-time · Entry level
$26.5 to $45.25 USD / hour
Posted yesterday
Source: Workday
Hybrid / On-site
The Netherlands +16 more
Full-time
Salary unavailable
Posted yesterday
Source: Ashby