Machine Learning Engineer, Spotify

Personalization

$138.3-197.5k

+ Equity. Salary applicable to US applicants only

Tensorflow

Kubeflow

PyTorch

Senior and Expert level

New York

Remote from Canada, US

More information about location

Commercial music streaming service

Be an early applicant

Commercial music streaming service

1001+ employees

B2CMusicEntertainmentDigital MediaSaaSMobile

Be an early applicant

$138.3-197.5k

+ Equity. Salary applicable to US applicants only

Tensorflow

Kubeflow

PyTorch

Senior and Expert level

New York

Remote from Canada, US

More information about location

1001+ employees

B2CMusicEntertainmentDigital MediaSaaSMobile

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

Job

Company

Role

Who you are

You have experience being a technical leader or mentor
You have a strong background in machine learning, especially experience with recommender systems
You have experience in designing and building ML systems at Spotify (including experience in spotify-kubeflow and salem)
You are experienced with feature engineering and building scalable data pipelines in Scio
You have a deep understanding of ML systems and infrastructure
You have experience in Tensorflow or PyTorch. Experience with Kubeflow, Ray is a plus

What the job involves

The Personalization team makes deciding what to play next on Spotify easier and more enjoyable for every listener
We seek to understand the world of music, podcasts, and audiobooks better than anyone else so that we can make great recommendations to every individual person and keep the world listening
Every day, hundreds of millions of people all over the world use the products we build which include destinations like “Home” and “Search” as well as original playlists such as “Discover Weekly” and “Daily Mix.”
Hulk stands for Human Understandable Language Knowledge. The team owns critical assets that power recommendation and distribution across Spotify
We are part of the LLM Foundations Product Area, and we heavily use modern AI techniques and LLMs to derive the best possible understanding of content and set up reliable and scalable systems for distributing that knowledge across partner Spotify teams
Be a technical leader within the team you work with and within Spotify in general
Coordinate technical projects across teams within Spotify
Facilitate collaboration with other engineers, product owners, and designers to solve interesting and challenging problems for delivering various media worldwide
Be a valued member of an autonomous, cross-functional agile team
Architect, design, develop, and deploy ML models that will serve podcast recommendations across the Home, Podcast Subfeed, and NPV surfaces
Be a leader in Home’s ML community and work collaboratively and efficiently within Home’s existing platforms and systems

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

Top investors

23% employee growth in 12 months

Glassdoor (4)

Trustpilot (1.7)

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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