Lead a team of machine learning engineers responsible for sourcing and shaping candidate inventory for Reddit's personalized feeds. Responsibilities include defining technical vision and roadmap for Feed Retrieval, overseeing design and optimization of retrieval systems, establishing measurement and experimentation practices, collaborating with ML platform and product teams, maintaining system performance and reliability, and recruiting/hiring. Qualifications include 2+ years managing ML or recommender-systems teams and hands-on experience with large-scale production ML (recommenders, embeddings, transformers/LLMs). Base salary range listed: $253,300–$354,600 USD per year.

Manage the Feed Ecosystems team to define technical vision and roadmap for recommender-system investments; oversee design and delivery of ML systems for cold-start relevance, post/community distribution, and feed quality; partner with product, design, data science, safety, ads, and platform teams; and hire and develop ML engineering talent. Requires 2+ years leading ML or recommender-systems teams and hands-on experience with large-scale production ML.

Senior technical role owning measurement, identity resolution, and signal strategy for Reddit Ads. Responsibilities include designing probabilistic identity models, owning lift and experimentation methodologies, quantifying and incorporating new signals into predictive models, and defining evaluation frameworks. Requires an advanced degree (MS or PhD) with significant industry experience, strong statistical programming (Python or R) and SQL skills, and expertise in measurement, experimentation, and predictive modeling.

Role focuses on end-to-end development of forecasting and scenario models for advertising—connecting supply, demand, audience, and response prediction. Responsibilities include model design, evaluation (accuracy, calibration, uncertainty), deployment, monitoring, and cross-functional collaboration to improve advertiser planning and investment decisions.

Lead technical direction and hands-on development (approx. 50% leadership/mentorship, 50% individual contributor) of content- and behavior-based embeddings and representation systems for ads, including multimodal embeddings, sequence models, knowledge-graph embeddings, and LLM/VLM-based representations. Requires 7+ years experience in end-to-end ML model lifecycle, strong background in content-rich NLP/CV at scale, familiarity with recommender/search/ads, and experience with frameworks such as PyTorch or TensorFlow.

The role leads technical strategy and execution for Ads Foundational Representations: building embeddings (text, media, knowledge graph, user intent) and related data and inference pipelines, working with LLMs/VLMs, and owning evaluation and experimentation. Requires 7+ years of ML lifecycle experience, staff-level technical leadership, strong experience with content-rich NLP/CV at scale, and familiarity with recommender/search/ads systems.

Join Reddit's Agentic Ads Experience team to build AI-powered advertiser-facing systems (campaign assistants, creative generation, audience discovery, analytics, optimization). Role involves end-to-end product execution, architecting agentic/LLM workflows, building reliability and guardrails, defining measurement and evaluations, and cross-functional collaboration. Requires 5+ years as a software engineer and hands-on experience building generative AI applications.

Senior Staff ML Engineer responsible for defining and building Reddit's unified user representation layer—including large-scale embeddings, interest modeling, and LLM-enhanced profiles—ensuring storage, feature pipelines, low-latency serving, and cross-team adoption across Feeds, Search, Notifications, and Ads. Role requires 10+ years building production ML systems and expertise in user modeling, representation learning, recommender systems, and applying LLMs/foundation models.

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.

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.