Senior Staff Machine Learning Engineer, ML Understanding

Details

Reddit is looking for a Senior Staff Machine Learning Engineer to lead the next-generation user understanding initiative: building a unified, high-fidelity representation of each user that powers personalization across the platform. This role is remote within the United States and will shape how hundreds of millions of people experience Reddit across Feeds, Search, Notifications, and Ads.

Responsibilities

• Define a unified user understanding framework and long-term technical vision: how users are represented (embeddings, tags, attributes, LLM-based user profiles), how they are computed, stored, and exposed.
• Lead design and implementation of advanced user models: large-scale user representation learning (sequence-based, multi-interest, multi-task) that share representations across product surfaces, balancing latency, cost, and performance.
• Reimagine user understanding with LLMs/GenAI: evolve user modeling by leveraging LLMs and foundation models for dynamic user profiles, intent inference, and semantic reasoning over user behavior.
• Ship large-scale user understanding as a system: partner with platform teams to design and build core components for large-scale learning and serving including storage/retrieval for embeddings, feature pipelines, and APIs.
• Collaborate with ML/ranking infrastructure to ensure low-latency serving, high availability, and integration with MLOps systems.
• Drive cross-team integration and adoption: work with Feeds, Notifications, Search, and Ads teams to run experiments and measure end-to-end impact on metrics like engagement and retention.
• Set technical bar and mentor: lead design reviews, mentor senior to staff engineers, steward technical decisions, and promote engineering best practices.

Requirements

• At least 10 years of experience building and scaling production-grade ML systems, particularly in user modeling, large-scale representation learning, or recommender systems.
• Deep expertise in mainstream user understanding ML approaches (representation learning, behavioral modeling, user clustering) and ability to judge trade-offs in real-world systems.
• Experience or strong intuition applying LLMs and foundation models to evolve existing systems (dynamic profiles, intent inference, semantic reasoning).
• Systems thinking across data, training, evaluation, serving, and adoption; experience designing end-to-end ML systems with considerations for latency, cost, safety, and reliability.
• Experience partnering with product, infrastructure, and other ML teams; track record driving ambiguous, high-impact initiatives from concept to production.
• Product- and impact-oriented: focus on measurable metrics (engagement, retention, revenue) in addition to model quality.

Benefits

• Comprehensive healthcare benefits and income replacement programs
• 401(k) with employer match
• Global benefit programs (workspace, professional development, caregiving support)
• Family planning support and gender-affirming care
• Mental health and coaching benefits
• Flexible vacation and paid volunteer time off
• Generous paid parental leave

Pay Transparency

• Base salary range for U.S.-based candidates: $266,000 - $372,400 USD
• Role may also be eligible for equity (RSUs) and, depending on position offered, commission

Additional Notes

• The posting notes interviews may be recorded/transcribed/summarized by AI with an opt-out opportunity.
• The role explicitly focuses on user understanding, embeddings, LLMs/foundation models, feature pipelines, storage/retrieval for embeddings, low-latency serving, and MLOps integration.