Reddit

Staff Machine Learning Engineer, Consumer

Lead · Удалённо · США · Английский B2

Навыки

  • AI-инструменты в работе
  • Airflow
  • BigQuery
  • Распределённые системы
  • Дообучение моделей
  • Go
  • Kafka
Ещё 12
  • Лидерство
  • LLM
  • Machine Learning
  • NLP
  • Python
  • PyTorch
  • RAG
  • Рекомендательные системы
  • Redis
  • Spark
  • TensorFlow
  • Transformers / HuggingFace

О компании и продукте

  • We are hiring Machine Learning Engineers across our Consumer Engineering organization, giving you the opportunity to work on a wide range of high-impact problems across the Consumer ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you

Задачи

  • We are looking for a Staff Machine Learning Engineer to help drive the next generation of Reddit’s ML ecosystem across recommendations, search, messaging, and foundational AI systems
  • You will lead high-impact initiatives from ideation to production, shaping both technical strategy and product direction across multiple ML domains
  • This is a highly cross-functional role partnering with Product, Data Science, and Engineering to deliver meaningful user and business impact
  • This role sits at the intersection of
  • Relevance & recommendation systems (content, search, notifications)
  • AI-powered discovery & LLM-driven experiences
  • Content and user understanding & large-scale representation learning
  • Large-scale ML infrastructure and pipelines
  • 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
  • Reddit is a community of communities
  • It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet
  • Every day, Reddit users submit, vote, and comment on the topics they care most about

Требования

  • 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

Будет плюсом

  • 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
  • Potential Teams
  • Home Experience
  • ML Understanding
  • Feed Relevance
  • Answer Experience
  • Search and Answers Relevance
  • Search Experience

Условия

  • 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
  • Flexible Vacation & Paid Volunteer Time Off
  • Generous Paid Parental Leave
  • With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information
  • For more information, visit www.redditinc.com
  • At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations
  • From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning

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