Machine Learning Engineer, Spotify

User Fraud

Salary not provided

AWS

GCP

Python

Scala

Tensorflow

PyTorch

Junior, Mid and Senior level

London

More information about location

Commercial music streaming service

Be an early applicant

Commercial music streaming service

1001+ employees

B2CMusicEntertainmentDigital MediaSaaSMobile

Be an early applicant

Salary not provided

AWS

GCP

Python

Scala

Tensorflow

PyTorch

Junior, Mid and Senior level

London

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

If you're excited by adversarial modelling, anomaly detection, and building systems that defend one of the world's leading streaming platforms, we'd love to hear from you
You have a strong background in machine learning, theory, and practice
You are comfortable explaining the intuition and assumptions behind ML concepts
You have hands-on experience implementing and maintaining production ML systems in Python, Scala, or similar languagesExperience with TensorFlow or Pytorch
You are experienced with building data pipelines, and you are self-sufficient in getting the data you need to build and evaluate your modelsYou preferably have experience with cloud platforms like GCP or AWS
You care about agile software processes, data development, reliability, and focused experimentation
You focus on delivering the simplest solution that drives business impact

What the job involves

We are seeking a Machine Learning Engineer to join the User Fraud R&D Studio at Spotify. Our mission is to protect Spotify from fake accounts and artificial streaming
You’ll work in a fast-moving team that experiments, iterates, and deploys innovative fraud prevention solutions
This includes analysing diverse user behaviours, uncovering patterns of abuse, and developing robust, scalable ML models that power real-time and batch decisions
Contribute to designing, building, evaluating, shipping, and refining Spotify’s anti-fraud product by hands-on ML development
Collaborate with a multi-functional team spanning data science, product management, and engineering to combat fraud
Prototype new approaches and productionise solutions
Help drive optimisation, testing, and tooling to improve quality
Be part of an active group of machine learning practitioners in your mission and across Spotify
Conduct analyses to gain insights on fraudulent behaviours and trends
Be responsible for monitoring the quality and performance of the squad's ML models

Salary benchmarks

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 (1.6)

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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