Reddit, Inc.

Security Engineer

• Build and evolve secure frameworks, guardrails, and library-level controls that make common vulnerability classes harder to introduce.
• Design security controls for AI-assisted development — including reusable rule packs and skills that shape how engineers and coding agents generate, review, and ship code.
• Embed security into the workflows engineers already use.
• Drive product security reviews for new launches and major architectural changes.
• Identify and eliminate systemic security debt.
• Shape strategy, influence architecture, and drive execution across teams.

Staff Product Security Engineer

Product Manager

• Define and lead a bold, long-term vision and strategy for AI-powered platform capabilities and API experiences for the third-party (3P) ecosystem
• Provide product thought leadership by identifying partner and developer needs through deep customer insights, ecosystem feedback, and market research
• Identify and incubate new platform opportunities informed by customer and partner research, competitive analysis, and industry trends
• Drive the team towards execution breaking down the strategy to longer term roadmap and quarterly OKRs. Manage the product launch process and continuously monitor performance, iterating towards the north star goal.
• Utilize data analytics and customer feedback to identify pain points, opportunities, and areas for improvement. Able to make trade-offs backed by a clear decisioning process.
• Build strong relationships and collaborate with engineering, Data science, UX, marketing and Sales teams to ensure alignment.
• As a senior member of the Product Management team and the product owner, you’ll regularly communicate across functions and the entire ads team, including frequently presenting to C-level executives.

Staff Product Manager, Ads API

Machine Learning Engineer

• Design, build, and deploy production-grade machine learning models and systems at scale
• Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring
• Build scalable data and model pipelines with strong reliability, observability, and automated retraining
• Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems.
• Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions
• Improve system performance across latency, throughput, and model quality metrics
• Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment
• Contribute to technical strategy, architecture, and long-term ML roadmap

Senior Machine Learning Engineer

Engineering Manager

• Steer: Work with the team to select, scope, and drive high leverage projects that align with Reddit’s goals.
• Build: Build out your team to execute on a strategy and create more efficient, more reliable Storage systems.
• Amplify: Mentor your ICs and be a leader for the team.
• Collaborate: Work together with a variety of teams across Reddit Engineering.
• Evolve: Learn and improve your own technical and non-technical abilities.

Engineering Manager, Search Storage

• Provide technical leadership and mentorship to MLEs and SWEs doing ML work in ACU, acting as de facto tech lead for content understanding and signals: driving design reviews, setting technical standards, and uplifting the team’s modeling and systems craft.
• Develop evaluation systems and quality monitoring systems for content understanding signals, using SOTA LM-judge practices.
• Drive operational excellence for ACU’s ML systems by defining SLOs, alerting, and dashboards for key signals (coverage, latency, precision/recall, cost)
• Build and evolve content understanding capabilities for commercial conversations (e.g., reviews vs. recommendations vs. comparisons vs. Q&A; sentiment and stance; product entities and categories) and operationalize them as robust signals that power contextual and shopping ads, auto-targeting, new formats, and insights products.
• Lead design and implementation of signals pipelines and produce an ACU signals registry. Partner with platform teams and other content understanding teams to ensure efficient, reliable serving at Reddit scale.
• Drive LLM and modern ML best practices within ACU: define when to prompt, finetune, or distill; design evaluation and safety harnesses; and lead at least one major distillation effort to replace external APIs with in-house models.
• Operate across the full ML lifecycle (problem framing, data, modeling, evaluation, deployment, monitoring, and oncall), designing scalable, resilient MLOps pipelines and championing responsible AI (bias, safety, explainability) for ACU’s models and signals in production.

Staff Machine Learning Engineer, Ads Content Understanding

• Design and ship the next generation ranking and ML backend systems that power discovery of Dev Platform apps and games across Reddit surfaces.
• Partner with ML, DS, and product to define signals, APIs, and feedback loops.
• Explore and productionize new retrieval, ranking, and experimentation approaches.
• Champion reliability, observability, and experimentation best practices.
• Write efficient, scalable code in our Go/Python/Baseplate/GraphQL stack.
• Mentor engineers and lead technical discussions.

Staff Machine Learning Engineer, Developer Platform

Android Engineer

• Video Ads Tech Lead: Partner closely with Product and Design to build a roadmap that will transform our Video Ads format into an industry leader in the space, and drive the technical design and execution of projects that turn the roadmap into reality.
• Technical Strategy: Provide guidance to the team working on building video ads as well as reddit-unique ad formats that scale to millions of users, by establishing Android best practices and providing design reviews.
• Full-Cycle Leadership: Drive the entire development lifecycle—from early-stage discovery and prototyping to testing, data-driven experimentation, and deployment.
• Raise the Bar: Mentor senior engineers across teams in ad formats and establish best practices for design, testing and operational excellence, while also leading by example in understanding and advocating for our customers.

Staff Android Engineer, Brand Ad Formats

• 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

Senior Staff Machine Learning Engineer, ML Understanding

• Lead the team that architects and designs notifications relevance at Reddit.
• Guide team on holistic, adaptive systems covering budgeting optimization, candidate retrieval, and ranking.
• Work with ML engineers to design, implement, and optimize machine-learning models that drive personalization and user re-engagement.
• Participate in the full development cycle: design, develop, QA, experiment, analyze, and deploy.
• Build and maintain a diverse team that can collaborate across disciplines to find technical solutions to complex challenges.
• Serve as a thought partner to product and upper management to ensure your team’s plans align with company goals.
• Communicate your team’s work and set expectations with cross-functional stakeholders.
• Help your engineers identify career goals and create development plans to achieve them.
• Constantly seek opportunities to push your engineers & managers outside their comfort zone and turn followers into leaders.

Machine Learning Manager, Notifications Relevance

Data Scientist

• Drive the adoption of strategic and tactical recommendations that are based on (1) deep and hands-on experience with Reddit products, and (2) data skills and understanding, to maximize our value to Reddit consumers.
• Serve as a thought-partner for product managers, engineering managers and leadership from your respective product domain, communicating and shaping the roadmap and strategy for Reddit by identifying actionable and impactful insights through deep-dive analyses and analytics insights.
• Be proactively involved in all phases of product development, including but not limited to, ideation, exploratory analysis, opportunity sizing, metrics design, offline modeling, experimentation and decision-making, post-launch monitoring/measurements etc.
• You will have a keen interest in the collection and quality of underlying data (experiment design and analysis, data deep dive), along with working on ETLs, reporting dashboards and data aggregations needed for business tracking and/or ML model development.

Data Science Manager, Consumer

• Contribute to advancing Reddit's Search and Recommendations products by designing AI-driven Search experience prioritizing seamless and delightful user experience.
• Deeply understand the Reddit search product and drive the vision for the search relevance team.
• Enhance core search retrieval and ranking, design and implement new search engine features, build and scale search indexes, develop and test new pipeline components. You will also deploy ML models, integrate LLMs, and ensure robust monitoring and smooth product integration throughout the process.
• Collaborate across disciplines and with ML, Product, Infrastructure, and DS teams at Reddit to find technical solutions to complex challenges.
• Mentor and guide senior and staff engineers in the team.
• Influence org-wide technical direction and partner closely with senior leadership to shape the long-term roadmap

Senior Staff ML Engineer, Search & Recommendation

• The EM will lead a diverse, high-impact team and will need to navigate and foster collaboration with various teams such as PM, DS, and engineering functions within Ads. Ideal candidates will have:
• People Management Experience: Prior experience managing engineering teams with a strong emphasis on technical mentorship and team growth.
• Set Technical Vision and Strategy: Ability to plan and execute a long-term technical strategy aligned with business objectives. Define and execute a roadmap for conversion modeling, balancing innovative modeling approaches with business objectives.
• Drive Technical Execution: Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.
• Lead and Mentor a High-Performing Team: Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.
• Collaborate Cross-Functionally: Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.
• Innovate in ML Architecture: Implement and optimize model architectures tailored to conversion prediction, leveraging deep learning and advanced ML techniques.

Staff Product Security Engineer

Staff Product Manager, Ads API

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Engineering Manager, Search Storage

Staff Machine Learning Engineer, Ads Content Understanding

Staff Machine Learning Engineer, Developer Platform

Staff Android Engineer, Brand Ad Formats

Senior Staff Machine Learning Engineer, ML Understanding

Machine Learning Manager, Notifications Relevance

Data Science Manager, Consumer

Senior Staff ML Engineer, Search & Recommendation

Ads Conversion Modeling, Machine Learning Engineering Manager