Machine Learning Engineer, Audience Intelligence New at Reddit
Ontario, Ontario, Canada -
Full Time


Start Date

Immediate

Expiry Date

13 Sep, 25

Salary

112500.0

Posted On

15 Jun, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description

Reddit is a community of communities. It’s built on shared interests, passion, and trust and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 101M+ daily active unique visitors, Reddit is one of the internet’s largest sources of information.
Reddit has a flexible-first workforce!
The Ads Targeting team’s mission is to develop robust, scalable, and privacy-compliant targeting products that enable advertisers to effectively reach relevant users. We are evolving to become the Audience Intelligence Engine, the central nervous system for user understanding in Reddit’s advertising ecosystem. Our goal is to synthesize a multitude of signals into unified, real-time, and privacy-compliant user profiles that power everything from targeting and ranking to forecasting and insights

Responsibilities

ABOUT THE ROLE:

As a Machine Learning Engineer on our Audience Intelligence team, you will play a pivotal role in this transformation. You will be responsible for designing and developing the machine learning models that generate new user intelligence at scale. This is a highly collaborative role where you will focus on modeling excellence and partner tightly with the team’s software engineers to integrate your model-produced intelligence into the broader advertising ecosystem. Your work will directly enhance our ability to understand users and improve advertiser outcomes.

RESPONSIBILITIES:

  • Design and develop machine learning models to infer and assess user attributes (e.g. Age, Gender, Language,In-Market status, etc)
  • Utilize diverse signals – including on-platform behavior (1P), off-platform partner data (3P), and contextual cues – to create predictive features for your models.
  • Conduct and analyze offline and online experiments to validate the impact of new intelligence features on Targeting Products and downstream parts of the serving ecosystem.
  • Partner closely with software engineers to deploy your models and ensure the intelligence they produce is successfully integrated into our real-time user profiles.
  • Collaborate with the Ads Privacy team to ensure all models and data handling practices are secure and compliant with policies like GDPR, CCPA, and ATT.
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