Machine Learning Engineer, Spotify
Personalization
More information about location
Commercial music streaming service
Be an early applicant
Commercial music streaming service
1001+ employees
Be an early applicant
More information about location
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 a strong background in machine learning, enjoy applying theory to develop real-world applications, with experience and expertise in bandit algorithms, LLMs, general neural networks, and/or other methods relevant to recommendation systems
- You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages. Experience with TensorFlow, PyTorch, Scikit-learn, etc. is a strong plus
- You have some experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, or even our open source API for it - Scio, and cloud platforms like GCP or AWS
- You care about agile software processes, data-driven development, reliability, and disciplined experimentation
- You love your customers even more than your code
What the job involves
- The Personalization team makes decisions about what to play next easier and more enjoyable for every listener
- From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features
- We built them by understanding the world of music and podcasts better than anyone else
- We are looking for a Machine Learning Engineer II to join our product area of hardworking engineers that are passionate about connecting new and emerging creators with users via recommendation algorithms
- As an integral part of the squad, you will collaborate with engineers, research scientists and data scientists in prototyping and productizing state-of-the-art ML
- Contribute to designing, building, evaluating, shipping, and refining Spotify’s personalization products by hands-on ML development
- Collaborate with a cross functional agile team spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and relevant ways
- Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users
- Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization
- Be part of an active group of machine learning practitioners in Europe (and across Spotify) collaborating with one another
- Together with a wide range of collaborators, help develop a creator-first vision and strategy that keeps Spotify at the forefront of innovation in the field
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 values
- Innovative: We move fast and take big risks
- Sincere: We have no time for internal politics
- Passionate: We revel in what we do
- Collaborative: We recognise that we're all in this together
- Playful: We don't take ourselves too seriously
Company HQ
Norrmalm, Stockholm, Stockholms län
Articles
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.
People progressing
Joined as a Conversion Manager in the Growth Team. Promoted three times over seven years to Senior Director - Head of Growth.
Joined as a Customer Advisor. Since then has had the role titles Senior Advisor, Content Associate, Team Coach, and Operations Manager - Primary Support. Hurst is now currently the Business Operations Manager of Music.
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