Senior Machine Learning Engineer, Ads
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.
About the job
What You’ll Work On
As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including:
- Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities
- Intelligent advertising systems including ranking, bidding, measurement, and optimization
- Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals
- Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems
- Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement
What You’ll Do
- 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
Basic Qualifications
- 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
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 (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
Benefits
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
Skills
Python, Java, Go, PyTorch, TensorFlow, Xgboost, Transformers, Cnns, Gnns, Spark, Kafka, Ray, Airflow, BigQuery, Redis
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