Staff Machine Learning Engineer, Consumer

Reddit is a community-driven platform that facilitates open conversations online. They are seeking a Staff Machine Learning Engineer to lead high-impact machine learning initiatives, focusing on recommendations, search, and user engagement across their Consumer Engineering organization.

Responsibilities:

• Lead end-to-end ML initiatives from ideation through production and iteration, shaping technical direction and translating product goals into scalable solutions
• Architect, build and deploy large-scale ML systems across recommendation, search, and content/user understanding, including retrieval/ranking models, representation learnings embeddings optimizations, and LLM or GenAI-powered capabilities
• Drive measurable impact on user engagement, discovery, and long-term value
• Collaborate with cross-functional teams to align product and technical roadmaps and unlock key future ML capabilities
• Stay at the forefront of AI research, evaluating and introducing new AI/ML paradigms to keep Reddit’s ML ecosystem at the cutting edge
• Contribute to the development of best practices, guidelines, and ethical AI principles for responsible LLM development and deployment
• Mentor and guide senior and mid-level ML engineers, fostering a culture of excellence, innovation, and knowledge sharing
• Set technical vision and drive technical discussions, present findings to leadership, and contribute to long-term ML planning and decision-making

Requirements:

• 7+ years of experience building, deploying, and operating machine learning systems in production
• Deep understanding of machine learning methods, spanning classical approaches and modern deep learning (e.g., Transformers, GNN, etc)
• Expert at developing and productionizing models using TensorFlow, PyTorch, or Hugging Face Transformers
• Experience building production-quality code incorporating testing, evaluation, and monitoring using object-oriented programming, including experience in Python and Golang
• Experience designing and scaling ML systems, including data pipelines, feature engineering, model training/serving, and production monitoring
• Excellent communication and collaboration skills, with the ability to discuss complex technical topics with diverse teams and translating product needs into scalable ML solutions
• Track record of driving measurable impact through applied machine learning in real-world products
• Subject matter expertise in one of the following domains: Recommender systems, Search systems (lexical and semantic retrieval and ranking), Content understanding (NLU/NLP/LLM, topic/taxonomy modeling, interest graphs or clustering, and multimodal understanding)
• Familiarity with distributed systems and large-scale data processing frameworks (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)
• Experience working with real-time systems and low-latency production environments
• Experience with LLM/GenAI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale
• Strong experimentation rigor, with experience formulating clear hypotheses, designing actionable learning plans and building offline/online correlations
• Advanced degree in Computer Science, Machine Learning, or related quantitative field