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About the Role
At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning.
We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for engineers who are excited to build systems end-to-end, from research and modeling to production deployment, and who want to help shape the future of discovery, relevance, and monetization at Reddit.
What You’ll Work On
As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including:
- Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities
- Intelligent advertising systems including ranking, bidding, measurement, and optimization
- Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals
- Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems
- Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement
Potential teams include Ads Measurement Modeling, Ads Targeting and Retrieval, Advertiser Optimization, Ads Marketplace Quality, Ads Creative Effectiveness, Ads Foundational Representations, Ads Content Understanding, Ads Ranking, Feed Relevance, Search and Answers Relevance, ML Understanding, and Notifications Relevance.
Key Technical Responsibilities
- check_circle Design, build, and deploy production-grade machine learning models and systems at scale
- check_circle Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring
- check_circle Build scalable data and model pipelines with strong reliability, observability, and automated retraining
- check_circle Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems
- check_circle Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions
- check_circle Improve system performance across latency, throughput, and model quality metrics
- check_circle Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment
- check_circle Contribute to technical strategy, architecture, and long-term ML roadmap
Prerequisites & Qualifications
- check 3-5+ years of experience building, deploying, and operating machine learning systems in production
- check Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
- check ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)
- check Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
- check Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure
- check Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions
- check Experience improving measurable metrics through applied machine learning
- check Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems is preferred
- check Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)
- check Advanced degree in Computer Science, Machine Learning, or related quantitative field
About Reddit Greenhouse Board
Verified hiring organization details.
Reddit Greenhouse Board serves as the hiring entity and recruitment portal for Reddit in Amsterdam, Netherlands. Reddit is a prominent social media and technology platform that hosts a vast network of online communities where users can share content, news, and discussions on a wide variety of topics.