Reddit, Inc.

Product Designer

• Be a strategic problem solver, identifying non-obvious opportunities to improve Reddit’s ads platform and ad experiences.
• Collaborate closely with product managers, engineers, researchers, data scientists, and other cross-functional partners to understand user needs, business goals, and technical constraints.
• Translate complex problems into elegant, scalable, and intuitive product experiences.
• Execute across every stage of the design lifecycle, from early concepts and systems thinking through detailed workflows and polished delivery.
• Drive alignment across diverse teams through strong exploration, storytelling, communication, and presentation to peers and leadership.

Senior Product Designer, Ads Measurement

Frontend Engineer

• Work cross-functionally, collaborate and partner with product, design, and other engineering counterparts to build novel products and features that our users will love.
• Work alongside a team of thoughtful, fast-moving, and motivated engineers. Contribute to standards that improve developer workflows, recommend best practices, and help mentor engineers on the team to grow their technical expertise.
• Own the full development cycle for major projects: design, development, test, experimentation, analysis, and launch. You’ll be writing and reviewing code and design docs, giving feedback on product specs and mocks, and ensuring successful delivery of these key projects.
• You will be a key driver in the planning, development, and implementation of critical projects across Reddit’s web architecture, working alongside backend and other client engineers.
• Enable a culture of metrics led execution, with a focus on operational excellence and system observability.
• Partner with leadership and cross-functional partners to develop the right roadmap that best achieves our product and engineering goals.

Senior Frontend Software Engineer, Home Experience

Affiliate Manager

• Translate complex data into clear, actionable narratives for senior leaders, HRBPs, and Talent partners.
• Utilize expertise to design innovative and competitive compensation programs that align with and support the company's business strategy.
• Partner with stakeholders across various functions to plan, develop, implement, and administer compensation programs.

Lead, Compensation Partner

Machine Learning Engineer

• Design, build, and deploy industrial-level machine learning models to solve critical problems in ad ranking, bidding, and optimization.
• Take full ownership of the ML lifecycle, from ideation and research to building scalable serving systems and maintaining models in production.
• Perform systematic feature engineering to transform raw, diverse data into high-quality features that drive model performance.
• Work closely with product managers, data scientists, and engineers to translate business challenges into effective ML solutions.
• Improve the reliability and stability of our ML systems by building robust monitoring, alerting, and automated retraining pipelines.
• Research new algorithms, stay up-to-date with state-of-the-art ML techniques, and contribute to the team’s strategy and roadmap.

Machine Learning Engineer, Ads

Senior Machine Learning Engineer, Ads

• Lead the building, testing, and maintenance of ML training infrastructure at Reddit.
• Play a pivotal role in designing, building, and optimizing the infrastructure and tooling required to support large-scale machine learning workflows.
• Evolve the MLE experience, from provisioning interactive GPU environments through large-scale training, supporting on-demand and self-service workflows.
• Kubernetes Automation: Write custom Kubernetes Controllers and Operators to manage the lifecycle of interactive Jupyter workspaces and long-running ML training jobs, handle auto-idling, and ensure fault tolerance.
• GPU Orchestration: Work with the underlying compute team to ensure MLEs have efficient access to training hardware resources and handle resource contention gracefully.
• Developer Experience (DevX): Treat internal MLEs as your customers. Conduct user research, reduce friction in the "Idea-to-Prototype" loop, and standardize software environments (Docker images, Python dependency management).

Senior Machine Learning Engineer, ML Training Platform

Financial Planning and Analysis

• Drive revenue outcomes by optimizing supply, demand, and pricing dynamics across ads products and sales channels
• Develop and execute yield strategies that maximize long-term revenue, not just short-term gains
• Monitor marketplace health (fill, density, pricing, ad performance) and proactively identify optimization opportunities
• Translate auction dynamics into predictive models that inform revenue forecasting and capacity planning
• Develop frameworks to quantify revenue ceilings, constraints, and trade-offs across the marketplace
• Create dashboards and tooling that provide visibility into revenue performance and inventory utilization
• Partner with Product to shape auction mechanics, ranking systems, and monetization features
• Size and evaluate new product opportunities, acting as a strategic advisor on revenue impact
• Collaborate with Sales leadership to inform channel strategy, pricing guidance, and packaging decisions
• Work closely with Sales, Product, Data Science, and Finance to align on ads marketplace strategy
• Support the investments, development, and rollout of automated systems (e.g., forecasting, allocation, pricing tools)
• Lead deep-dive analyses that inform executive decision-making and investment prioritization
• Educate Sales and cross-functional partners on auction ad marketplace dynamics and revenue optimization best practices
• Simplify complex marketplace concepts into clear, actionable insights for executive audiences

Strategic Finance, Yield Manager

Data Scientist

• Design, develop, and apply DS solutions to inform improvements in advertiser experience and Reddit's ad platform
• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Collaborate with product managers and engineers to define product requirements and translate them into data science solutions
• Develop ML models &amp; DS methods to improve anomaly detection, prediction, &amp; pattern recognition
• Communicate findings and recommendations to stakeholders across the organization
• Stay up-to-date on the latest advancements in machine learning and data science
• Mentor and guide junior data scientists on the team

Senior Data Scientist, Ads

• Help build the long term product strategy by identifying opportunities to attract new users, increase engagement, and drive retention
• Influence strategic roadmaps through data-driven insights into user behaviors and needs
• Design metrics that help evaluate the health of the business and the success of our products, including any ETL development needed for consistent and robust analysis
• Drive experimentation from design through execution and analysis to maximize learnings and guide future investment decisions
• Build self-serve tools for product and engineering partners that answer common questions and/or increase data literacy in the organization
• Work cross functionally with product, engineering, and design teams to ensure insights make it to the product
• Scale your work to other parts of the data organization through mentoring more junior data scientists, improving processes, and providing perspective on the most important problems

Staff Data Scientist, Consumer

• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Develop ML models & DS methods to for improved anomaly detection, prediction, pattern recognition
• Communicate findings and recommendations to stakeholders across the organization
• Collaborate with product, engineering, sales, and marketing partners to define product and program requirements and translate them into data science solutions
• Stay up-to-date on the latest advancements in machine learning and data science

Data Scientist, Ads

• 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

Technical Program Manager

• Identify Opportunities. You don’t wait for others to bring problems to you. You understand the business deeply and proactively find opportunities to automate and improve the user experience.
• Get Things Done. More than just building decks or delivering regular updates. You actually bring projects to completion, deliver real accomplishments for the business, and help your teams and stakeholders understand the difference.
• Dive into Details. You understand the details of their projects and help guide them in active partnership with their teams. You don’t just stay high level or leave the details for other teams to figure out. You have the technical judgment to act as a partner with your teams in planning and decision-making.
• Make Work Repeatable. You create and improve processes that light the path for others and prevent and remove recurring organizational toil. You set standards for the organization and aid in the adoption of these standards where relevant.
• Mentor & Lead. You excel at influencing others in developing key organizational and project deliverables. You’re a leader within your projects and support people in the process.
• Bring Order out of Chaos. You are known for leaving a program and the teams you support in a position of stronger organization than where they started, and those teams continue to succeed even when you are no longer specifically engaged in the project.

Senior Technical Program Manager, Go-To-Market Systems

Senior Frontend Software Engineer, Feeds Experience

Product Manager

• Define and evangelize a 3-year roadmap.
• Own the full funnel, including business identity dashboards, verification, campaign management, and deep-funnel performance reporting.
• Ensure our API ecosystem remains robust and at parity with our UI.
• Lead and scale a high-performing organization of Product Managers.
• Act as the strategic lead unifying multiple cross functional teams for a cohesive user experience.
• Drive product strategy for internationalization and agency-specific features.

Senior Director of Product, Ads Platform

• 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