Senior Machine Learning Engineer - Ads R&D at Spotify

New York, New York, United States

Spotify Logo
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Advertising, TechnologyIndustries

Requirements

  • Professional experience in applied machine learning
  • Strong technical expertise in software engineering, data analysis, and machine learning
  • Proficient in programming languages such as Python, Java, or Scala
  • Experienced in TensorFlow or PyTorch and working with various aspects of the ML lifecycle
  • Expertise in developing data pipelines using tools like Apache Beam or Spark
  • Strong expertise in data analysis, online experimentation techniques, and large-scale ML and engineering systems
  • Motivated by user and business problems as well as technical problems
  • Thrives under ambiguity, experimentation, and iteration
  • Ability to work in the Americas region and U.S. Eastern time zone for collaboration
  • As a plus: experience with LLMs, Ray, Adtech, or Recommender Systems

Responsibilities

  • 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
  • Work directly on an array of product features that drive the optimal user experience for ads
  • Collaborate with cross-functional teams to ideate, develop, and own complex technical solutions on ad services technology platforms

Skills

Machine Learning
Multi-Task Learning
Transformer Architectures
Causal Inference
Online Experimentation
Data Analysis
Large-scale ML Systems

Spotify

Digital music streaming service with podcasts

About Spotify

Spotify provides a digital music streaming service that allows users to access millions of songs and podcasts from various artists and creators. Users can choose between a free plan, which includes advertisements, and a premium subscription that offers an ad-free experience along with features like offline listening and higher sound quality. This tiered model caters to different user preferences and budgets. Spotify generates revenue through subscription fees from premium users and advertising from the free tier. Unlike its competitors, Spotify stands out with its extensive music library, user-friendly interface, and personalized playlists. The company's goal is to connect listeners with a wide range of audio content while supporting artists and advertisers.

Stockholms kommun, SwedenHeadquarters
2006Year Founded
$2,004.2MTotal Funding
IPOCompany Stage
Consumer Software, EntertainmentIndustries
10,001+Employees

Benefits

Extensive learning opportunities, through our dedicated team, GreenHouse
Global parental leave, six months off - fully paid - for all new parents
Flexible public holidays, swap days off according to your values and beliefs
Flexible share incentives letting you choose how you share in our success
All The Feels, our employee assistance program and self-care hub
Spotify On Tour, join your colleagues on trips to industry festivals and events

Risks

Accidental display of adult content may harm Spotify's reputation.
Creating its own music to avoid royalties could lead to legal issues.
Layoffs may affect Spotify's operational efficiency and employee morale.

Differentiation

Spotify offers a vast library of music and podcasts globally.
The platform's user-friendly interface enhances user experience and engagement.
Spotify's personalized playlists cater to individual user preferences.

Upsides

Spotify's AI-powered Wrapped feature enhances user engagement and personalization.
Expansion into political podcasting taps into new audience segments.
Growing podcast popularity in Africa presents expansion opportunities for Spotify.

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