Senior ML engineer focused on improving training and inference efficiency for Reddit's Ads ML models. Own optimization initiatives, diagnose production bottlenecks, build reusable tooling and primitives, and mentor others on measurable efficiency and launch-safety wins.
Build, train, and optimize large language models and ML systems to scalably enforce Reddit's community rules and keep users safe. Requires 5+ years MLE experience with NLP, deep learning frameworks, and distributed training.
Senior Machine Learning Engineer building and shipping production ML systems for Ads Content Understanding at Reddit. Focus on LLMs, content taxonomies, opinion mining, product understanding, and operationalizing signals for monetization impact. Requires 5+ years delivering scalable ML in production.
Build and evolve auction, bidding, and budgeting ML systems that power Reddit Ads. Design optimization algorithms balancing advertiser performance, user experience, and marketplace efficiency.
Build large-scale ML experimentation and training orchestration platforms, including agentic AI execution systems, to accelerate Ads ML development at Reddit. Requires 5+ years infrastructure experience and 2+ years building production ML platforms.
Technical leader for Reddit's Notifications Relevance ML systems, driving large-scale recommendation systems spanning retrieval, ranking, budget optimization, and LLM-powered experiences.
Design, build, and deploy production ML systems for recommendations, search, ranking, and advertising at internet scale. Own the full ML lifecycle from modeling to monitoring with strong cross-functional collaboration.
Design and build scalable ML ranking systems powering Reddit's personalized feeds, search, and recommendations at massive scale. Requires 5+ years building large-scale distributed ML systems.
Own evaluation science and post-training methodology for Reddit's foundational LLMs. Define benchmarks, design model-as-a-judge systems, and set SFT recipes that turn base models into safe, Reddit-native endpoints.
Staff ML Systems Engineer leading large-scale embedding and recommendation model architecture, distributed training, and real-time serving. Owns ML strategy and mentors engineers on personalization systems.
As a Senior Staff Machine Learning Engineer, you will design and build large-scale, end-to-end recommendation systems for Reddit's Notifications Relevance team. You will leverage machine learning and LLMs to deliver personalized content to users, driving growth and user engagement.
Lead Reddit’s Safety ML organization to build and deploy large-scale ML systems that detect harmful content and protect users. Drive strategy, manage teams of 25+ ML scientists and engineers, and partner cross-functionally to advance responsible AI for platform safety.
Leads development of security-focused ML models for GenAI traffic at Reddit, owning the full ML lifecycle from data ETL to production deployment and monitoring. Requires 5+ years experience with PyTorch/TensorFlow, deep learning architectures, and MLOps for adversarial security risks.
Leads technical strategy, architecture, and development of advanced ML models for ads identity modeling and measurement, ensuring scalability, privacy compliance, and integration across systems. Requires 7+ years software engineering with 3+ in ML at scale, expertise in ML frameworks and large-scale data processing.
Leads design and implementation of advanced user modeling systems using ML and LLMs to create unified user representations for personalization across Reddit's Feeds, Search, Notifications, and Ads. Requires 10+ years in production ML, especially user understanding and recommender systems.
Designs and builds large-scale ML systems for Reddit's search relevance, including query understanding, retrieval, ranking, and LLM integration. Requires 10+ years in search/recommendation systems, ML model deployment, and cross-team collaboration.
Leads machine learning team developing conversion models for Reddit Ads, focusing on predictive modeling for user actions like purchases and signups. Requires deep ML expertise, ads domain knowledge, and 2+ years managing high-performing ML teams.
Leads end-to-end ML initiatives for Reddit's consumer features like recommendations, search, and AI discovery. Requires 7+ years experience with deep learning frameworks, production ML systems, and expertise in Transformers, LLMs, or recommender systems.
Builds and scales Generative AI platform infrastructure using advanced ML techniques. Requires deep expertise in large-scale model training, deployment, and optimization on cloud platforms.
Leads development of Reddit's large-scale GenAI Platform, including LLM Gateway, RAG applications, and agentic AI workflows. Requires 5+ years in ML/AI platform engineering with expertise in cloud, Kubernetes, and MLOps practices.
Leads development of large-scale ML platforms, focusing on MLOps, graph ML infrastructure, performance optimization, and distributed training pipelines. Requires 8+ years in ML infrastructure with expertise in Python, PyTorch, Kubernetes, Ray, and cloud tools.
Leads development of large-scale ML platforms, focusing on MLOps, graph ML infrastructure, performance tuning, and distributed training optimization. Requires 5+ years in ML infrastructure with expertise in PyTorch, Kubernetes, Ray, and cloud tools.
Senior ML engineer focused on improving training and inference efficiency for Reddit's Ads ML models. Own optimization initiatives, diagnose production bottlenecks, build reusable tooling and primitives, and mentor others on measurable efficiency and launch-safety wins.
Build, train, and optimize large language models and ML systems to scalably enforce Reddit's community rules and keep users safe. Requires 5+ years MLE experience with NLP, deep learning frameworks, and distributed training.
Senior Machine Learning Engineer building and shipping production ML systems for Ads Content Understanding at Reddit. Focus on LLMs, content taxonomies, opinion mining, product understanding, and operationalizing signals for monetization impact. Requires 5+ years delivering scalable ML in production.
Build and evolve auction, bidding, and budgeting ML systems that power Reddit Ads. Design optimization algorithms balancing advertiser performance, user experience, and marketplace efficiency.
Build large-scale ML experimentation and training orchestration platforms, including agentic AI execution systems, to accelerate Ads ML development at Reddit. Requires 5+ years infrastructure experience and 2+ years building production ML platforms.
Technical leader for Reddit's Notifications Relevance ML systems, driving large-scale recommendation systems spanning retrieval, ranking, budget optimization, and LLM-powered experiences.
Design, build, and deploy production ML systems for recommendations, search, ranking, and advertising at internet scale. Own the full ML lifecycle from modeling to monitoring with strong cross-functional collaboration.
Design and build scalable ML ranking systems powering Reddit's personalized feeds, search, and recommendations at massive scale. Requires 5+ years building large-scale distributed ML systems.
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Own evaluation science and post-training methodology for Reddit's foundational LLMs. Define benchmarks, design model-as-a-judge systems, and set SFT recipes that turn base models into safe, Reddit-native endpoints.
Staff ML Systems Engineer leading large-scale embedding and recommendation model architecture, distributed training, and real-time serving. Owns ML strategy and mentors engineers on personalization systems.
As a Senior Staff Machine Learning Engineer, you will design and build large-scale, end-to-end recommendation systems for Reddit's Notifications Relevance team. You will leverage machine learning and LLMs to deliver personalized content to users, driving growth and user engagement.
Lead Reddit’s Safety ML organization to build and deploy large-scale ML systems that detect harmful content and protect users. Drive strategy, manage teams of 25+ ML scientists and engineers, and partner cross-functionally to advance responsible AI for platform safety.
Leads development of security-focused ML models for GenAI traffic at Reddit, owning the full ML lifecycle from data ETL to production deployment and monitoring. Requires 5+ years experience with PyTorch/TensorFlow, deep learning architectures, and MLOps for adversarial security risks.
Leads technical strategy, architecture, and development of advanced ML models for ads identity modeling and measurement, ensuring scalability, privacy compliance, and integration across systems. Requires 7+ years software engineering with 3+ in ML at scale, expertise in ML frameworks and large-scale data processing.
Leads design and implementation of advanced user modeling systems using ML and LLMs to create unified user representations for personalization across Reddit's Feeds, Search, Notifications, and Ads. Requires 10+ years in production ML, especially user understanding and recommender systems.
Designs and builds large-scale ML systems for Reddit's search relevance, including query understanding, retrieval, ranking, and LLM integration. Requires 10+ years in search/recommendation systems, ML model deployment, and cross-team collaboration.
Leads machine learning team developing conversion models for Reddit Ads, focusing on predictive modeling for user actions like purchases and signups. Requires deep ML expertise, ads domain knowledge, and 2+ years managing high-performing ML teams.
Leads end-to-end ML initiatives for Reddit's consumer features like recommendations, search, and AI discovery. Requires 7+ years experience with deep learning frameworks, production ML systems, and expertise in Transformers, LLMs, or recommender systems.
Builds and scales Generative AI platform infrastructure using advanced ML techniques. Requires deep expertise in large-scale model training, deployment, and optimization on cloud platforms.
Leads development of Reddit's large-scale GenAI Platform, including LLM Gateway, RAG applications, and agentic AI workflows. Requires 5+ years in ML/AI platform engineering with expertise in cloud, Kubernetes, and MLOps practices.
Leads development of large-scale ML platforms, focusing on MLOps, graph ML infrastructure, performance optimization, and distributed training pipelines. Requires 8+ years in ML infrastructure with expertise in Python, PyTorch, Kubernetes, Ray, and cloud tools.
Leads development of large-scale ML platforms, focusing on MLOps, graph ML infrastructure, performance tuning, and distributed training optimization. Requires 5+ years in ML infrastructure with expertise in PyTorch, Kubernetes, Ray, and cloud tools.