Lead and grow a machine learning engineering team focused on engagement and conversion prediction for Reddit Ads. Responsibilities include technical vision, overseeing end-to-end model development and deployment, mentoring engineers, and collaborating with product, data science, and engineering partners. Requires management experience (2+ years), deep hands-on ML expertise, and 4+ years with TensorFlow or PyTorch.

Work on Reddit's Notifications Relevance team to design and implement large-scale recommendation systems (retrieval, ranking, budget optimization), deploy ML models and LLMs in production, ensure monitoring and product integration, and mentor senior/staff engineers. Requires 10+ years' industry experience with large-scale recommendation systems and experience with PyTorch/TensorFlow, Python and/or Golang.

Lead model development and MLOps for GenAI Security at Reddit: define problems, assemble and label datasets, build ETL and training pipelines, train and evaluate deep learning models (transformers, embeddings, sequence models), deploy and monitor production models, and partner with cross-functional teams. Requires 5+ years of production ML/deep learning experience and hands-on use of frameworks such as PyTorch or TensorFlow.

Lead design and implementation of search relevance, retrieval, ranking, and ML-driven search features (including LLMs and RAG). Requires 10+ years experience in large-scale search/recommendation systems, proficiency with PyTorch or TensorFlow, production LLM experience, and programming in Python and/or Golang. Remote role for United States-based candidates.

Lead the Conversion Modeling team at Reddit (remote in the U.S.), owning technical vision and execution for production-scale conversion prediction models (ranking/recommendation). Requires deep ML and deep learning expertise, experience with TensorFlow/PyTorch, data pipelines, production model lifecycle, and at least 2+ years managing or tech-leading ML engineering teams. Posted salary range: $230,000–$322,000 USD per year.

Senior Staff Machine Learning Engineer to define and lead Reddit’s GenAI Platform vision, design and operate a unified LLM Gateway (APIs, rate/token limits, failover), set MLOps/LLMOps standards (CI/CD, testing, versioning, evaluation), and drive platform architecture for scalability, reliability, and observability. Requires 10+ years experience and deep production experience with Kubernetes and cloud ML infrastructure.

Senior (Staff) ML engineering role at Reddit working end-to-end on large-scale ML systems across recommendation, search, messaging, and foundational AI. Responsibilities include architecting and deploying retrieval/ranking and representation learning models, productionizing LLM/GenAI capabilities, driving measurable user impact, mentoring engineers, and contributing to technical strategy and responsible AI practices. Requires 7+ years of production ML experience and hands-on experience with TensorFlow/PyTorch/Hugging Face, Python and Golang.

Lead design and implementation of Reddit's platform for large-scale ML models, including end-to-end MLOps (data prep, experiment tracking, model management), distributed GPU training, and graph ML pipelines. Role expects 8+ years in ML infrastructure with experience in cloud tools (GCP BigQuery, Google Cloud Storage), infrastructure-as-code (Terraform), MLOps tools (MLflow/Wandb), Python and ML frameworks (PyTorch/TensorFlow), and distributed frameworks (Ray, Kubernetes). Experience with graph databases and GNN frameworks is a plus.

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 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.

Lead the Embeddings Platform team at Reddit to design, implement, and maintain large-scale embedding systems (graph neural networks, transformer/sequence models, foundational models). Responsibilities include platform architecture, enabling ML engineers and data scientists, driving scalable and reliable production ML systems, and growing a high-performing team through hiring and mentorship.

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.