Staff Machine Learning Engineer (Consumer)

Location: Remote - United States

Base salary: $230,000–$322,000 USD per year, plus potential equity and commission depending on the position offered.

Company

Reddit is a large-scale community platform where machine learning powers content discovery, recommendations, search, advertising, and user engagement.

What you will do

• Lead machine learning initiatives from ideation through production and ongoing iteration.
• Architect, build, deploy, and operate large-scale systems for recommendations, search, content understanding, and user understanding.
• Develop retrieval and ranking models, representation learning and embedding optimizations, and LLM- or GenAI-powered capabilities.
• Partner with Product, Data Science, and Engineering to align roadmaps and deliver measurable user and business impact.
• Evaluate emerging AI and ML paradigms and establish responsible practices for LLM development and deployment.
• Set technical vision, present findings to leadership, and mentor senior and mid-level machine learning engineers.

Requirements

• 7+ years of experience building, deploying, and operating production machine learning systems.
• Deep knowledge of classical machine learning and modern deep learning methods, including Transformers and GNNs.
• Expertise with TensorFlow, PyTorch, or Hugging Face Transformers.
• Production-quality object-oriented programming experience with Python and Golang, including testing, evaluation, and monitoring.
• Experience designing and scaling data pipelines, feature engineering, model training and serving, and production monitoring.
• Strong communication, collaboration, and applied machine learning impact track record.

Nice to have

• Expertise in recommender systems, search and retrieval, or content understanding using NLU, NLP, LLMs, topic modeling, clustering, or multimodal methods.
• Experience with Spark, Kafka, Ray, Airflow, BigQuery, Redis, or other large-scale data processing technologies.
• Experience with real-time, low-latency systems and LLM evaluation, alignment, fine-tuning, distillation, RAG, or agentic systems.
• Strong experimentation rigor and experience connecting offline and online evaluation.
• Advanced degree in Computer Science, Machine Learning, or a related quantitative field.

Culture & Benefits

• Comprehensive healthcare and income replacement programs.
• 401(k) with employer match and global benefits programs.
• Flexible vacation, paid volunteer time off, and generous paid parental leave.
• Family planning support, gender-affirming care, and mental health and coaching benefits.
• Benefits supporting workspace, professional development, and caregiving.

Hiring process

• Some interviews may be recorded, transcribed, and summarized by AI; candidates can opt out before scheduled interviews.