Greenhouse ·
full-timeSenior Staff Machine Learning Engineer, ML Understanding
Reddit · Remote - United States
Reddit operates a vast network of online communities centered on shared interests and authentic discussions. As a Senior Staff Machine Learning Engineer focused on ML Understanding, you will lead the technical strategy for building a unified, high-fidelity representation of the platform's user base. This role involves designing and implementing scalable systems that capture user interests, behavioral signals, and affinities to power personalization across feeds, search, notifications, and advertising. You will be responsible for evolving traditional user modeling techniques by integrating large language models and foundation models to improve intent inference and semantic reasoning. Day-to-day tasks include defining the architecture for embedding storage and retrieval, collaborating with infrastructure teams to ensure low-latency performance, and mentoring senior engineering staff. This position is ideal for an experienced machine learning practitioner with over a decade of experience in building production-grade recommendation systems and large-scale representation learning. The role suits a candidate who can bridge the gap between advanced research in generative AI and practical, high-impact product engineering to enhance the experience of millions of daily active users.
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 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . We’re looking for a Senior Staff Machine Learning Engineer to lead Reddit’s next-generation user understanding initiative: building a unified, high-fidelity representation of each user that powers personalization across the platform. This role requires deep expertise in mainstream ML user modeling approaches (e.g., large-scale embeddings, user interest modeling, affinities, behavioral signals) and the ability to reimagine these systems in the GenAI era—leveraging LLMs and foundation models to unlock step-change improvements in fidelity, adaptability, and expressiveness. You will set the technical direction for this space, leading the design and implementation of Reddit’s core user representation layer—spanning embeddings, interest modeling, and key user attributes. You’ll ensure this foundation is scalable, reliable, and widely adopted across Feeds, Search, Notifications, and Ads, partnering closely with product, infrastructure, and downstream ML teams to drive measurable impact. This is a high-impact role. The systems you build will shape how hundreds of millions of people experience Reddit every day—what they see, what they discover, and the communities they connect with. Your work will directly advance personalization and relevance at global scale, strengthening Reddit as a platform for meaningful connection and belonging. What you'll do: Design User Understanding Strategy: Define a unified user understanding framework and strategy: how users are represented (embeddings, tags, attributes, LLM-based user profile), how they are computed, stored, and exposed. Provide thought leadership in user understanding and user modeling by setting a long-term technical vision and advancing the state-of-the-art in the field. Build Foundational User Models: Lead design and implementation of advanced user models, e.g. large-scale user representation learning (sequence-based, multi-interest, multi-task) that share representations across surfaces to improve personalization experience across key Reddit products e.g. Feeds, Notification, Search and Ads, balancing latency, cost, and performance. Reimagine user understanding with LLM/Gen-AI: Evolve user modeling beyond traditional representations by leveraging LLMs to build richer user understanding (e.g., dynamic user profiles, intent inference, semantic reasoning over user behavior). Explore how LLMs can augment or unify embeddings, attributes, and taxonomies to enable more adaptive, interpretable, and context-aware personalization. Ship Large Scale User Understanding as a System: Partner with platform teams to design and build core components for large-scale learning and serving: storage/retrieval for embeddings, feature pipelines, and APIs. Collaborate with ML/Ranking infra to ensure low-latency serving, high availability, and integration with MLOps systems. Drive Cross-Team Integration & Impact: Partner with Feeds, Notification, Search and Ads teams to drive experimentation and adoption of new user understanding models with product teams across Reddit, ensuring measurable end-to-end impact on key metrics. Set Technical Bar & Mentor: Mentor senior to staff engineers, lead design reviews, steward technical decisions across the user understanding domain, and champion and drive engineering processes and best practices Who you might be: You have at least 10 years experience building and scaling production-grade ML systems, particularly in user modeling, large-scale representation learning, or recommender systems. You have a track record of driving ambiguous, high-impact initiatives from concept to production, shaping both technical direction and execution. You are product- and impact-oriented: you care deeply about how your work moves real metrics (e.g., engagement, retention, revenue), not just model quality. You bring strong fundamentals in mainstream user understanding ML approaches (e.g., representation learning, behavioral modeling, user clustering), and understand their trade-offs in real-world systems. You are excited about the GenAI shift and have experience (or strong intuition) applying LLMs or foundation models to evolve existing systems, going beyond incremental improvements. You think in systems, not just models: you consider data, training, evaluation, serving, and adoption as a cohesive whole, and design with end-to-end impact in mind. You influence beyond your immediate team: partnering effectively with product, infra, and other ML teams, and driving alignment across multiple stakeholders. You raise the technical ba
| Role | Senior Staff Machine Learning Engineer, ML Understanding |
|---|---|
| Company | |
| Location | Remote - United States |
| Compensation | Not disclosed |
| Posted | 2026-10-01 |
| Deadline | Rolling |
Typical process for this type of role
A general guide — the exact steps for this specific listing may vary; check the original posting for details.
- 1ApplicationSubmit your resume through the apply link.
- 2ScreeningRecruiter reviews your background against the role.
- 3AssessmentA technical test, assignment, or coding round, depending on the role.
- 4Interview(s)One or more rounds with the hiring team.
- 5OfferOffer letter with compensation and start date.
Before you apply
0/4Senior Staff Machine Learning Engineer, ML Understanding at Reddit: frequently asked questions
- What is the salary for this role?
- Reddit has not stated compensation in the listing. Check the original posting or ask during the application process.
- Is the Senior Staff Machine Learning Engineer, ML Understanding position remote, hybrid or onsite?
- The listing marks this role as remote, with Remote - United States as the location.
- What is the application deadline?
- Reddit has not listed a fixed deadline, so apply early in case the opening is filled.
- How do I apply for the Senior Staff Machine Learning Engineer, ML Understanding role?
- Use the Apply button on this page. It opens the original listing on job-boards.greenhouse.io, where you submit your application with the company.
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