Senior ML Infrastructure Engineer responsible for designing end-to-end model lifecycle patterns (MLOps), building and supporting graph ML codebases and platforms, optimizing distributed GPU training and batch data processing, and architecting pipelines for massive graph datasets. Role emphasizes scalability, reliability, performance, and collaboration with ML teams.

Remote staff role responsible for developing probabilistic identity resolution, advancing brand and conversion lift methodologies, designing evaluation frameworks and ground truth, defining and quantifying signal value for predictive models, and leading cross-functional initiatives. Requires an advanced degree (MS with 10+ years or PhD with 6+ years) and strong skills in statistical programming (Python/R), SQL, experimentation, causal inference, and machine learning.

Senior role owning measurement, identity resolution, experimentation methodology, and signal strategy to improve ad performance and attribution. Requires an advanced degree (M.S. or Ph.D.) with substantial industry experience (Ph.D.: 6+ years; M.S.: 10+ years). Remote-friendly US position.

Reddit is hiring a Staff Product Designer for the Growth team (remote, US). The role leads end-to-end growth work across multiple surfaces, shapes strategy and roadmaps, builds high-fidelity prototypes using code, runs rapid experimentation and A/B tests, and raises design systems and component quality. Requires 8+ years of product design experience and experience operating at Staff scope. Listed US base salary range: $194,600–$272,400 USD per year.

Remote (United States) senior role focused on refining and owning Reddit’s data storage and caching infrastructure to support hundreds of millions of users. Requires 5+ years building internet-scale software and experience with distributed storage, languages such as Golang/Python/C++/Java, and storage technologies like Postgres, MySQL, Cassandra, Redis, and Memcached.

Mid-level generalist backend role on Reddit Ads. Responsibilities include designing and implementing advertiser-facing microservices and APIs, building distributed and real-time data systems, improving operational stability, and collaborating with product, platform, and data teams. Requires 3+ years of software development experience in languages such as Java, Scala, Go, C++, or Python.

Mid-level backend engineer role on Reddit Ads teams (e.g., Ads ML Serving, Attribution & Identity, Ads Growth, Business Manager). Work includes building microservices/APIs, distributed and real-time data systems, and infrastructure for ad products using technologies such as Go, Python, Scala, Spark, Kafka, Postgres, BigQuery, Redis, Druid, Kubernetes, Argo, and Docker. Requires 3+ years of software development experience.

Generalist mid-level backend role in Reddit's Ads organization. Responsibilities include designing and implementing ads products and microservices, collaborating with platform and data teams, improving operational stability (code quality, dashboards), and building extensible components. Technologies mentioned: Go, Python, Scala, Spark, Thrift, Baseplate, Kafka, Postgres, BigQuery, Redis, Druid, Kubernetes, Argo, Docker.

Generalist senior backend engineer role on Reddit's Ads organization responsible for building microservices and APIs, distributed and real-time data systems, ad backends and interactive ad experiences. Technologies listed include Go, Python, Scala, Spark, Kafka, Postgres, BigQuery, Redis, Druid, Kubernetes, Argo and Docker. Requires 5+ years of software development experience. US-based remote; base salary range $190,800–$267,100 USD per year.

Reddit is hiring a Senior Machine Learning Engineer to own end-to-end ML systems including model development, scalable data and model pipelines, model serving, and monitoring. The role focuses on recommendations, search/ranking, advertising systems, representation learning and LLM/Gen AI techniques, and requires production ML experience, strong software engineering skills, and familiarity with modern ML frameworks and large-scale data processing tools.

Reddit seeks a Senior Machine Learning Engineer to own end-to-end ML systems—from problem definition and feature engineering to training, deployment, and monitoring—focusing on recommendations, search/ranking, advertising systems, representation learning, and LLM/GenAI techniques. Requires production ML experience (3+ years), strong programming skills, and familiarity with ML frameworks and large-scale data/serving infrastructure.

Senior Data Scientist role on the Ads Data Science team at Reddit (remote, US). Responsibilities include designing and applying ML and statistical models, analyzing large-scale datasets, defining metrics, running experimentation (A/B testing/causal inference), and mentoring junior data scientists. Qualifications call for an advanced quantitative degree and multiple years of applied data science experience; platform and large-scale data tools experience (Spark/Hadoop/Hive/BigQuery), plus proficiency in Python/R, SQL, and ML libraries are emphasized.

Lead the Ads Data Science strategy and roadmap, design large-scale statistical, econometric, causal and ML solutions (e.g., LTV, auction/auctioning, targeting, full-funnel models), partner with Product/Engineering/Analytics Engineering, and mentor senior data scientists. Requires an M.S. (12+ years) or Ph.D. (8+ years) in a quantitative field and advanced proficiency in Python or R and SQL.

Seeking a Machine Learning Engineer to design, build, and operate end-to-end ML systems (recommendation, search/ranking, ads, content/user understanding, and LLM/GenAI features). Requires ~3+ years building production ML (Python/Java/Go), experience with ML frameworks (PyTorch/TensorFlow), scalable pipelines, model serving, and working with large datasets.

Reddit seeks a Machine Learning Engineer to own the full ML lifecycle—designing, training, deploying, and monitoring scalable models and pipelines for personalization, search/ranking, advertising systems, content/user understanding, and applied LLM work. Requires 3+ years of production ML experience and hands-on work with ML frameworks and large-scale data systems.