RedditPosted today
Staff Machine Learning Engineer, App Ads Modeling at Reddit scores 91 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
Reddit has a flexible first workforce!
We’re looking for a Staff-level Machine Learning Engineer to join Reddit’s Ads Ranking Org. This role is part of a broader effort to enhance Reddit’s ML-powered ad ranking systems through improved model architectures, contextual embeddings, and conversion-optimized modeling.
The ideal candidate will bring strong end-to-end modeling expertise, a deep understanding of modern deep learning techniques, and a passion for building systems that drive measurable impact in ads marketplaces. While ads experience is a plus, strong modelers from recommendation systems, search relevance, or other performance-driven domains are encouraged to apply. This position will sit on the App Ads Modeling team and report directly into the Ranking Org.
Responsibilities:
- Design and train advanced ML models (e.g., DNNs, transformers) to power Reddit Ads Ranking
- Develop and optimize features including embeddings, contextual signals, and cross-session behavior
- Work closely with product, infra, and data teams to drive end-to-end model deployment and performance analysis
- Mentor other MLEs and contribute to modeling best practices across the org
- Shape the long-term modeling vision across one or more domains (conversion, app ads, shopping, brand, etc.)
Required Qualifications:
- 7+ years of industry experience, including several years in applied ML roles
- Strong experience with Deep Learning architectures and ML frameworks (TensorFlow, PyTorch)
- Strong background in recommendation systems, ads ranking, or similar domains
- Experience working with large-scale datasets and complex feature pipelines
- Strong problem-solving and experimentation skills
- State of the Art models for Ads or Recsys experience (ex: Transformers, Recsys)
- Knowledge about Recsys or Ads funnel
- Track record of delivering high-impact models in production settings
- Comfort collaborating with infra and data teams on feature serving and training pipelines
Preferred Qualifications:
- Experience with conversion modeling, app ads, or performance/brand ads
- Experience in ads marketplaces at peer companies
- Publications, patents, or industry contributions in applied ML or ranking systems
Benefits:
- 100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago)
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
#LI-AJ1
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.
To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
The base salary range for this position is:$230,000—$322,000 USDIn select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
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- What's a project where you used PyTorch hands-on?
- Walk me through how you've used TensorFlow in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
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- List these exact terms on your resume: PyTorch and TensorFlow. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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