Senior Machine Learning Engineer, Spotify

Ads R&D

$176.2-251.7k

+ Equity. Salary applicable to US applicants, may vary for other locations

Python

Scala

Java

Tensorflow

Spark

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

$176.2-251.7k

+ Equity. Salary applicable to US applicants, may vary for other locations

Python

Scala

Java

Tensorflow

Spark

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

We are looking for someone with strong expertise in data analysis, online experimentation techniques, and large-scale ML and engineering systems; someone who is motivated by user and business problems as much as they are by technical problems, and who thrives under ambiguity, experimentation, and iteration
As someone who shares our passion for building innovative ad experiences, you'll have a direct impact on how the world uses Spotify
You have professional experience in applied machine learning
You have strong technical expertise in software engineering, data analysis, and machine learning
You are proficient in programming languages such as Python, Java, or Scala
Experienced in Tensorflow or PyTorch and working with various aspects of the ML lifecycle
You have expertise in developing data pipelines using tools like Apache Beam or Spark
As a plus, you may have experience with any of the following - LLMs, Ray, Adtech, or Recommender Systems

What the job involves

We are seeking a Senior Machine Learning Engineer to join the Ad Engagement squad. Ad Engagement focuses on using machine learning to accurately predict how Spotify listeners will react to ads, helping advertisers minimize their costs while delivering a more relevant and enjoyable ad experience for listeners
Our core innovations include Multi-Task Learning models (MTL), and we are expanding into scalable sequence modeling with complex transformer architectures
Recently, we presented a paper about this in KDD Toronto and you can check out the latest details in the blog post here
We are also seeking a Senior Machine Learning Engineer to join the Supply Personalization squad. Supply Personalization focuses on optimizing the volume, timing, and types of ad loads a user receives
By leveraging data, machine learning, causal inference, and large scale online experimentation, we aim to uncover and learn the most effective strategies for enhancing user experiences and driving business outcomes
You will work directly on an array of product features that drive the optimal user experience for our ads
You will collaborate with our cross-functional teams to ideate, develop, and own complex technical solutions on our ad services technology platforms
Design and implement machine learning systems for ad performance optimization
Research and apply ML optimization strategies to balance multiple objectives effectively
Work on a paradigm shift modeling work for Ads that involves working on Sequence Transformer model for User-Ad Interaction, that works along a MTL model
Analyze data and use machine learning techniques to understand user behavior and improve ad experiences
Collaborate with backend engineers, data scientists, data engineers, and product managers to establish baselines, inform product decisions, and develop new technologies

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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