Staff Machine Learning Engineer, App Ads Modeling
Confirmed on the employer's own hiring board on Sep 25, 2026. First seen by Alion on Sep 25, 2026. Reddit scores B on the Alion truth index.
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 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.
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
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 USD
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