Senior Machine Learning Engineer

Reddit, Inc. is a community-driven platform built around shared interests, conversation, and trust, serving millions of daily visitors through a large network of communities. The Senior Machine Learning Engineer will design, build, deploy, and operate large-scale production machine learning systems spanning recommendations, search, advertising, content and user understanding, and LLM-powered experiences. The role owns the full ML lifecycle, develops scalable pipelines and infrastructure, partners cross-functionally, and advances ML strategy and system performance.

Responsibilities:

• Design, build, and deploy production-grade machine learning models and systems at scale
• Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring
• Build scalable data and model pipelines with strong 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, and LLM evaluation/alignment
• Contribute to technical strategy, architecture, and long-term ML roadmap

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: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (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
• • 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 (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)
• • Experience working 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 but not limited to 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