Staff Machine Learning Engineer, Dev Platform Data and Discovery
RedditRemote - United StatesPosted 7 April 2026
Tech Stack
Job Description
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 121 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com .
The Developer Platform team empowers developers to create engaging interactive experiences for Reddit communities, such as asynchronous or real-time multiplayer games, live stock tickers, and live scoreboards. If you have a background in ranking and are excited about connecting Redditors with their next favorite game, this highly collaborative and impactful team wants your expertise!
You will own projects from ideation to production instead of being stuck making small incremental gains on enterprise systems. You’ll work with a super talented, cross-functional team to solve hard problems in order to create experiences that users will love. We are a team of builders that value impact, personal growth, openness and kindness.
Responsibilities:
Lead projects from concept, design, implementation, to rollout, ensuring the highest quality and performance.
Identify opportunities to enhance ranking capabilities by diving deep into our platform and understanding the needs of our customers.
Design and develop applied machine learning models for modeled personalization, game taxonomy, and more, from ideation to production deployment.
Collaborate with data scientists, product managers and backend software engineers.
Mentor junior team members, share knowledge, and contribute to the technical growth of the team. Provide guidance on machine learning best practices and methodologies.
Conduct A/B tests and experiments to iterate and fine-tune algorithms and models.
Stay updated on state-of-the-art algorithmic techniques and recognize promising innovations, adapting them to Reddit's unique platform and community.
Design, implement, and maintain reliable, high-performance distributed systems.
Minimum Qualifications:
5+ years of experience in a relevant industry or academic background, preferably in a quantitative/modeling or highly scalable computing environment.
Prior experience with personalized feed ranking.
Proven track record of delivering complex machine learning projects from conception to deployment, preferably in real-world applications.
Ability to lead and mentor machine learning engineers or data scientists.
Strong communication skills to collaborate effectively with cross-functional teams and stakeholders.
Demonstrated ability to innovate and stay updated with the latest advancements in machine learning and AI.
Preferred Qualifications:
Experience of orchestrating complicated data pipelines and system engineering on large-scale dataset
Proficiency with programming languages and statistical analysis
Prior experience with Sequence Modeling, Reinforcement Learning, or Transformer Architecture is a big plus
Experience in Bayesian methodology and experimentation is a plus
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.
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
Benefits:
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 ... (truncated, view full listing at source)
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