Senior Machine Learning Engineer

Details

Role Overview

Reddit is looking for a Senior Machine Learning Engineer to design and build production ML systems end-to-end—from research and modeling to production deployment. The role focuses on core experiences across Reddit’s platform, including recommendations, search and ranking, advertising systems, user/content understanding, and large-scale ML pipelines and real-time decision systems.

Responsibilities

• Design, build, and deploy production-grade machine learning models and systems at scale
• Own the full ML lifecycle: problem definition and feature engineering through training, evaluation, deployment, and monitoring
• Build scalable data and model pipelines with reliability, observability, and automated retraining
• Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems
• Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions
• Improve system performance across latency, throughput, and model quality metrics
• Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers-based approaches, and LLM evaluation/alignment
• Contribute to technical strategy, architecture, and long-term ML roadmap

What You’ll Work On

• Personalized recommendations, search, and ranking systems
• Intelligent advertising systems (ranking, bidding, measurement, optimization)
• Content, Advertisers, and User understanding (foundational content/user representations and signals)
• Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems
• Applied AI and LLM-driven experiences for relevance, discovery, and user engagement

Requirements

• 3-5+ years of experience building, deploying, and operating machine learning systems in production
• Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
• ML fundamentals, including classic statistical learning (e.g., XGBoost, Random Forests, regressions) and deep learning architectures (e.g., Transformers, CNNs, GNNs)
• Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
• Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure
• Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions
• Experience improving measurable metrics through applied machine learning

Preferred Qualifications

• Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems
• Familiarity with distributed systems and large-scale data processing (e.g., Spark, Kafka, Ray, Airflow, BigQuery, Redis)
• Experience with real-time systems and low-latency production environments
• Background in feature engineering, model optimization, and production monitoring
• Experience with LLM/Gen AI techniques including LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems, and productionizing LLM-powered products at scale
• Advanced degree in Computer Science, Machine Learning, or related quantitative field

Benefits

• Comprehensive healthcare benefits and income replacement programs
• 401k with employer match
• Global benefit programs (workspace, professional development, caregiving support)
• Family planning support
• Gender-affirming care
• Mental health & coaching benefits
• Flexible vacation & paid volunteer time off
• Generous paid parental leave