Staff Machine Learning Engineer, Ads Ranking

16 Minutes ago • 7 Years + • Research Development • $230,000 PA - $322,000 PA

Job Summary

Job Description

Reddit is seeking a Staff Machine Learning Engineer to enhance its Ads Ranking organization. This role involves improving ML-powered ad ranking systems through advanced model architectures, contextual embeddings, and conversion-optimized modeling. Responsibilities include designing and training models like DNNs and transformers for Reddit Ads Ranking, developing features such as embeddings and contextual signals, and collaborating with product, infra, and data teams for end-to-end model deployment. The engineer will mentor other MLEs, contribute to modeling best practices, and shape the long-term modeling vision across various ad domains. Key challenges include balancing generalization and specificity, managing model complexity versus performance, and cross-functional alignment for ML initiatives. This position offers direct impact on product and revenue, the opportunity to shape foundational ML modeling for Reddit Ads, flexible scope, and exposure to diverse ad surfaces and cutting-edge ML techniques. Reddit provides a supportive work environment, professional growth opportunities, competitive compensation and benefits, and flexible work arrangements.
Must have:
  • 7+ years of industry experience in applied ML roles
  • Deep experience with DNN architectures and ML frameworks (TensorFlow, PyTorch)
  • Strong background in recommendation systems or ads ranking
  • Experience with large-scale datasets and complex feature pipelines
  • Strong problem-solving and experimentation skills
Good to have:
  • Design and train advanced ML models for Ads Ranking
  • Develop and optimize features including embeddings and contextual signals
  • Collaborate with product, infra, and data teams for model deployment
  • Mentor other MLEs and contribute to modeling best practices
  • Shape long-term modeling vision across ad domains
Perks:
  • Comprehensive Healthcare Benefits and Income Replacement Programs
  • 401k Match
  • Family Planning Support
  • Gender-Affirming Care
  • Mental Health & Coaching Benefits
  • Flexible Vacation & Reddit Global Days Off
  • Generous paid Parental Leave
  • Paid Volunteer time off
  • Flexible work arrangements, including remote work options

Job Details

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. For more information, visit redditinc.com.

We’re looking for a Staff 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. This position allows the opportunity to contribute across key modeling focus areas such as conversion, app ads, shopping, brand ads, or core ranking.

What you bring:

  • 7+ years of industry experience, including several years in applied ML roles
  • Deep experience with DNN 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

Day-to-Day 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.)

Most Challenging Aspects:

  • Balancing generalization and specificity in modeling across different ad formats
  • Managing trade-offs between model complexity, latency, and prediction quality
  • Navigating cross-functional alignment to scale high-impact ML initiatives

What Differentiates This Role:

  • Direct path to measurable product and revenue impact
  • Opportunity to shape foundational ML modeling across Reddit Ads
  • Flexible scope based on modeling strengths (conversion, app ads, core ranking, etc.)
  • Exposure to diverse ad surfaces (feed, video, shopping, brand) and cutting-edge ML techniques

What We Offer:

  • A dynamic, supportive work environment with a diverse team of engineers and cross-functional partners
  • Opportunities for professional growth and development, with a focus on continuous learning and skill-building
  • A competitive salary and benefits package, with a focus on work-life balance and employee well-being
  • Flexible work arrangements, including remote work options, to support your individual needs and preferences
  • The chance to work on high-impact projects that drive real results for our users and advertisers

Benefits:

  • Comprehensive Healthcare Benefits and Income Replacement Programs
  • 401k Match
  • Family Planning Support
  • Gender-Affirming Care
  • Mental Health & Coaching Benefits
  • Flexible Vacation & Reddit Global Days Off
  • Generous paid Parental Leave 
  • Paid Volunteer time off

 

#LI-Remote

 

 

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 pay 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 pay range for this position is:

$230,000 - $322,000 USD

In select roles and locations, the interviews will be recorded, and transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out 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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About The Company

San Francisco, California, United States (On-Site)

San Francisco, California, United States (On-Site)

San Francisco, California, United States (On-Site)

San Francisco, California, United States (On-Site)

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