Role Description
We are looking for a Staff Machine Learning Engineer to help drive the next generation of Redditโs 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:
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Relevance & recommendation systems (content, search, notifications)
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AI-powered discovery & LLM-driven experiences
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Content understanding & representation
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Large-scale ML infrastructure and pipelines
If you love working on complex, real-world ML problems at massive scale, this role is for you.
What Youโll Do
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Architect, build, and deploy large-scale ML systems powering recommendations, search, messaging, and content understanding
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Lead projects from ideation โ modeling โ experimentation โ production โ iteration
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Design and improve recommender systems and ranking models across surfaces (feed, search, notifications)
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Optimize for user engagement, discovery, and long-term value
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Build next-gen AI-powered search and recommendation experiences, including LLM-integrated systems
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Develop pipelines that help users find high-quality answers and content across Redditโs corpus
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Build and optimize content embeddings and representation models for users, communities, and content
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Leverage and advance LLMs and multimodal models for deeper understanding and personalization
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Evaluate model performance, improve accuracy, and reduce bias
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Partner with Product, Data Science, Infra, and UX teams to solve complex problems
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Translate ambiguous business needs into scalable ML solutions
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Mentor engineers and raise the bar across the organization
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Establish best practices for ML development, experimentation, and responsible AI
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Act as a thought leader across teams and domains
Qualifications
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6+ years of experience building, deploying, and operating machine learning systems in production
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Strong programming skills in Python, Go, or similar languages, with solid software engineering fundamentals
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ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)
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Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
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Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure
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Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions
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Experience driving measurable impact through applied machine learning
Preferred Qualifications
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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.
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Familiarity with distributed systems and large-scale data processing frameworks (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)
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Experience working with real-time systems and low-latency production environments
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Background in feature engineering, model optimization, and production monitoring
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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
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Advanced degree in Computer Science, Machine Learning, or related quantitative field
Benefits
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Comprehensive Healthcare Benefits and Income Replacement Programs
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401k with Employer Match
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Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
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Family Planning Support
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Gender-Affirming Care
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Mental Health & Coaching Benefits
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Flexible Vacation & Paid Volunteer Time Off
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Generous Paid Parental Leave