- Company: Reddit
- Salary: Pay not listed
- Work type: Remote
Reddit at a glance
reddit.com- Founded 2005
SEC filings mentioning "reddit": 587 · SIC industry: Services-Computer Processing & Data Preparation — search EDGAR
Most recent 8-K (material company event) filed: Aug 12, 2026 — view filing
Private funding round disclosed to the SEC: $700.0M offering (filed 2021-08-26) — Form D filing
1,940 employees covered under a retirement plan (2024 filing) — via DOL Form 5500 / EFAST2
Registered as a global legal entity (LEI 529900APN1YHPBHPI679, US) — via GLEIF
183,927 Wikipedia views in July 2026 — a rough gauge of public visibility.
Staff Machine Learning Engineer, Ads Foundational Representations at reddit - Remote Full Time Position
What This Role Involves
The Ads Foundational Representations (AFR) team develops signals and representations of Reddit’s core entities (ads, posts, users, and so on), capturing the semantic, contextual, and behavioral information that Reddit Ads needs. We work on building embeddings to improve ad targeting, personalization, and overall user experience across the platform.
Responsibilities
- Develop and maintain advanced machine learning models for ads representation
- Create and optimize embeddings for various entities within the platform
- Collaborate with cross-functional teams to integrate new representations into ad systems
- Analyze data and provide insights to improve ad performance and user engagement
- Conduct experiments and research to drive innovation in ads technology
Who We're Looking For
We are seeking a highly skilled Staff Machine Learning Engineer with experience in building and deploying machine learning models for large-scale applications. You should have a strong background in natural language processing, deep learning, and embeddings. Experience working on distributed systems and familiarity with Python, TensorFlow, or PyTorch is essential.
Working at reddit
Reddit has a flexible first workforce. Don’t live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands. As a remote employee, you will have access to all the tools and resources needed to succeed in your role.
Applying for This Role
To apply, complete your application directly on this page, or you'll be redirected to the employer's application platform to finish submitting there. Please ensure you include a detailed resume and cover letter highlighting your relevant experience with machine learning models and embeddings.
You’ll finish your application on the employer’s website. We don’t ask for a resume on this page.
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What people say about Reddit
Recent news
- How Graham Platner's campaign unraveled: From Reddit posts to rape allegation - Fox News
- Reddit Is Cracking Down on AI Marketing Slop With Its Own AI - Bloomberg.com
- How We’re Keeping Reddit Real and Safe in the AI Era - Reddit Inc Homepage
- Employee emails HR about sick leave, their response leaves Reddit shaking their heads - India Today
- Reddit reports more than 23M daily spam views - Social Media Today
Aggregated from public discussions and news; opinions are the authors’ own.
Job details above are provided by the employer/source. The sections on this page are compiled from public data sources with AI assistance.
Accommodations: if you need a workplace accommodation to apply for or perform this job, see ADA.gov or EEOC.gov for guidance on your rights and how to request one.
Listing facts
- Role Staff Machine Learning Engineer, Ads Foundational Representations
- Employer Reddit
- Work mode Remote
- Type Full Time
- Pay (from listing) Pay not listed
- Posted August 16, 2026
- Apply by September 16, 2026
- Overview Full job description on this page (270 words)
Facts above come from this job record on Get A Job.AI — not copied from third-party review sites.
Public discussions & open sources
Attributed public threads and profiles — not employee reviews or star ratings.
- Hacker News — The Web We Have to Save
- Hacker News — Ask HN: Who is hiring? (August 2015)
- Hacker News — The Web We Have to Save
- Hacker News — The Web We Have to Save
Cached public sources (Hacker News, Dev.to, GitHub, etc.).
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