Staff Machine Learning Engineer

10h•Remote

About The Position

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. With 100,000+ active communities and approximately 121 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. We hire 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. 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 understanding & representation Large-scale ML infrastructure and pipelines

Requirements

6+ years of experience building, deploying, and operating machine learning systems in production
Strong programming skills in Python, 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 driving measurable impact through applied machine learning

Nice To Haves

Subject matter expertise in Recommender systems, search systems (lexical and semantic retrieval and ranking),, advertising/auction systems, large-scale representation learning, or multimodal embedding systems, content understanding etc.
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
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

Responsibilities

Architect, build, and deploy large-scale ML systems powering recommendations, search, messaging, and content understanding
Lead projects from ideation → modeling → experimentation → production → iteration
Design and improve recommender systems and ranking models across surfaces (feed, search, notifications)
Optimize for user engagement, discovery, and long-term value
Build next-gen AI-powered search and recommendation experiences, including LLM-integrated systems
Develop pipelines that help users find high-quality answers and content across Reddit’s corpus
Build and optimize content embeddings and representation models for users, communities, and content
Leverage and advance LLMs and multimodal models for deeper understanding and personalization
Evaluate model performance, improve accuracy, and reduce bias
Partner with Product, Data Science, Infra, and UX teams to solve complex problems
Translate ambiguous business needs into scalable ML solutions
Mentor engineers and raise the bar across the organization
Establish best practices for ML development, experimentation, and responsible AI
Act as a thought leader across teams and domains

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

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