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 [http://redditinc.com/].
Reddit has a flexible workforce! If you happen to live close to one of our
physical office locations our doors are open for you to come into the office as
often as you'd like. Don't live near one of our offices? No worries: You can
apply to work remotely in any country in which we have a physical presence.
Reddit is a community of communities where people can dive into anything through
experiences built around their interests, hobbies, and passions. Our mission is
to bring community, belonging, and empowerment to everyone in the world. Reddit
users submit, vote, and comment on content, stories, and discussions about the
topics they care about the most. From pets to parenting, there’s a community for
everybody on Reddit and with over 50 million daily active users, it is home to
the most open and authentic conversations on the internet. For more information,
visit redditinc.com.
Reddit is a network of more than 100,000 communities where people can dive into
anything through experiences built around their interests, hobbies and passions.
Reddit users submit, vote and comment on content, stories and discussions about
the topics they care about the most. From pets to parenting, there’s a community
for everybody on Reddit and with more than 100 million daily active uniques, it
is home to the most open and authentic conversations on the internet. For more
information, visit redditinc.com.
We’re evolving and continuing our mission to bring community, belonging, and
empowerment to everyone in the world. Providing a delightful and relevant
experience to our users applies to our Ads like all of our offerings, and we’re
excited to build a product that is best-in-class for our users and advertisers.
The year ahead is a busy one!
TEAM DESCRIPTION
Reddit is poised to rapidly innovate and grow like no other time in its history.
We’re currently hiring across multiple teams including: Ads Prediction, App Ads
& Conversion Modeling, Ads Measurement Modeling, Ads Targeting & Retrieval,
Advertiser Optimization and Ads Marketplace Teams.
Ads ML Serving Team
Part of Reddit’s Ads ML Platform, this team builds a highly reliable, scalable,
and efficient ML serving stack. They focus on long-term architecture, tight
integration with the ads serving stack, CPU/GPU performance optimization, and
model velocity tools like observability libraries and quality gating.
Attribution & Identity Team
This team builds attribution systems and identity solutions that help
advertisers measure the impact of their campaigns. They create experimentation
tools and platforms that improve usability, transparency, and performance
insights.
Ads Measurement Modeling Team
A horizontal ML team in the Ads Measurement org focused on proving Reddit Ads
value while maintaining privacy compliance. Their work includes Modeled
Identity, Modeled Conversions, and ATT opt-out utility enhancements.
Ads Targeting and Retrieval Team
This team designs and implements large-scale ML systems to improve targeting
products. They work on offline and online retrieval systems to enhance
contextual and behavioral targeting.
Advertiser Optimization Team
Composed of two horizontal teams, this group focuses on advertiser outcomes. The
Recommendations and Forecasting team builds ML-driven tools for advertisers and
sales. The Bidding/Pacing team develops algorithms and products like TCPA,
TROAS, and performance advertising solutions, while driving innovations in
marketplace dynamics.
Ads Marketplace Quality Team
This team optimizes Reddit’s ads marketplace by building algorithms for auction
and pricing efficiency. They also work on supply optimization and ad relevance,
ensuring ads reach the right users at the right time in the right context.
App Ads and Conversion Modeling Teams
Formed in early 2024, these teams focus on app ads modeling, including app
install models and deep neural network models for iOS and Android conversions.
They work on in-app event optimization and return on ad spend (RoAS)
optimization, and are running experiments on top of DNN architectures to improve
prediction accuracy.
Ads Prediction Team
This team drives innovation across signals, features, model architecture, and
infrastructure to improve marketplace efficiency and revenue. It includes:
- Core Ads Ranking (CAR): Builds reusable, scalable features and ranking models
that integrate across the ads ecosystem, improving quality and iteration
speed.
- Engagement Modeling (EV): Develops click, long-click, and video engagement
models for upper- and middle-funnel ad products.
The Ads Creative Effectiveness team
This team is a newly formed group aimed at improving ad creative at Reddit
through generative and predictive products. We train, adapt and finetune
LLMs/VLMs to help advertisers make impactful images, videos and text. We build
performance predictors to understand and rank ad components, ensuring the
advertiser ships the best possible campaigns. We construct insight and
recommendation engines to guide advertisers towards best practices and key
enhancements, distilling knowledge about what works at Reddit to supercharge
their performance.This team is at the heart of Reddit’s creative strategy, a
core priority for the organization.
Reddit Ads offers the opportunity to work on large-scale systems that directly
impact advertisers, users, and revenue. We have openings across multiple teams
and are looking for engineers and ML experts at all levels.
ROLE DESCRIPTION
Join the Ads team as a Machine Learning Engineer and become a key contributor to
Reddit’s business. In this hands-on role, you will be responsible for the full
lifecycle of our ML systems, from initial research and modeling to deployment
and optimization in production. Your work will directly impact how we deliver
relevant ads and drive value for our advertisers across areas like ad ranking,
bidding, measurement, and optimization.
RESPONSIBILITIES:
- Design, build, and deploy industrial-level machine learning models to solve
critical problems in ad ranking, bidding, and optimization.
- Take full ownership of the ML lifecycle, from ideation and research to
building scalable serving systems and maintaining models in production.
- Perform systematic feature engineering to transform raw, diverse data into
high-quality features that drive model performance.
- Work closely with product managers, data scientists, and engineers to
translate business challenges into effective ML solutions.
- Improve the reliability and stability of our ML systems by building robust
monitoring, alerting, and automated retraining pipelines.
- Research new algorithms, stay up-to-date with state-of-the-art ML techniques,
and contribute to the team’s strategy and roadmap.
REQUIRED QUALIFICATIONS:
- Experience working in the Ads domain
- At least 3-5+ years of end-to-end experience in training, evaluating, and
deploying machine learning models in a production environment.
- Proficient in one or more general-purpose programming languages (e.g.,
Python, Scala) and have a solid understanding of software development best
practices.
- Hands-on experience with a major machine learning framework (e.g.,
TensorFlow, PyTorch) and a deep understanding of core ML concepts and
algorithms.
- Proven ability to work effectively with cross-functional teams, including
product managers and data scientists, to translate business needs into
technical solutions.
- Track record of using machine learning to drive key performance indicator
(KPI) wins and solve complex, real-world problems.
BONUS POINTS:
- Experience or interest in the advertising business and understanding customer
needs
- An advanced degree (MS/PhD) in a quantitative field.
- Familiarity with distributed systems and large-scale data processing
technologies (e.g., Spark, Kafka).
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 [https://redditinc.com/policies/candidate-privacy-policy].
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.
