Staff Machine Learning Engineer, Spotify
Music Mission
$227.5-325k
Plus equity
Commercial music streaming service
Be an early applicant
Commercial music streaming service
1001+ employees
Be an early applicant
$227.5-325k
Plus equity
1001+ employees
Company mission
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 opportunity to enjoy and be inspired by it
Role
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
What the job involves
- 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
- 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
Our take
Spotify was founded in an attempt to combat the rampant music piracy that was causing significant harm to the industry. The company has since taken music streaming mainstream and now has 180m+ paying subscribers across the world.
With features that include a highly accessible interface and a vast catalogue of artists, Spotify's strong brand has been able to maintain growth in spite of fierce competition from deep-pocketed rivals like Amazon and Apple. The company has achieved this by making smart acquisitions to move into other verticals to strengthen its offerings, especially podcasting, by acquiring Gimlet Media, Anchor and Parcast.
Spotify's future plans include rapid growth with a goal to become a one-stop destination for all digital sound, as well as AI and NFT integrations. However, high costs incurred from the acquisition of exclusive podcasts, increasing competitor strength, and weak bottom-line growth mean that the company must find a balance to maintain its position in the sector.
Freddie
Company Specialist at Welcome to the Jungle
Insights
23% employee growth in 12 months
Company
Funding (last 2 of 8 rounds)
Jan 2016
$1bn
CONVERTIBLE
Jun 2015
$526m
SERIES G
Total funding: $2.1bn
Company 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 - fully paid - 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
Company HQ
Norrmalm, Stockholm, Stockholms län
Leadership
Daniel Ek
(CEO & Chairman)Founded Spotify in 2006. Previously worked as an executive at Tradera, an auction company that was sold to eBay and was briefly the CEO of uTorrent.
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