Senior Product Manager, ML Signals

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 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit we continue to grow our teams with the best talent. We're completely remote friendly . As a Senior Product Manager for ML Signals, you will define and execute the team roadmap by partnering closely with ML Signals Machine Learning Engineers, other surface consumer product managers, data scientists, and policy experts. With a strong background in the latest ML/AI research, you will lead the expansion of content understanding signals across all modalities, including text, image, and video, to support a unified multimodal representation of Reddit content. You will define the goals and success metrics, identify initiatives to achieve the goals and collaborate with cross functional partners to deliver these initiatives. You will be able to prioritize projects by what will have the most downstream impact and help drive adoption of these signals across the org. Responsibilities: Signal Strategy & Vision: Define the long-term roadmap for foundational "content understanding" signals, including topicality (interest-based tagging), content maturity, and quality scores used across the platform. Platform Adoption: Act as the primary bridge between the MLE team and downstream consumers (e.g., Feed, Ads, Search, and Safety). Drive the integration of ML signals to improve personalization and brand safety. Signal Governance: Establish standardized definitions and success metrics for content quality and utility, ensuring a consistent understanding of "high quality" across different product surfaces. Data Strategy & Labeling: Lead the strategy for high-quality training data, including the use of "Human-in-the-Loop" (HITL) workflows and modern automated evaluation techniques (e.g., using Large Language Models to assist in data labeling). Performance Optimization: Partner with Data Science and MLEs to monitor signal health, coverage, and accuracy (Precision/Recall), and translate technical performance into business impact (e.g., retention, engagement, or revenue). Cross-Functional Leadership: Navigate complex tradeoffs between Policy, Engineering, and Product teams to ensure signals meet both user safety requirements and product growth goals. Required Qualifications: Technical Leadership & Experience 5+ years of Product Management experience , specifically focused on Machine Learning, NLP, or Platform products. A proven history of shipping high-impact products that have delivered measurable business results. Autonomy in roadmap management , with the ability to lead complex services from initial vision to execution and scaling. Strategic vision , including the ability to define clear goals and success metrics that align with broader organizational objectives. Machine Learning Expertise Deep understanding of the ML lifecycle , encompassing data collection, feature engineering, model evaluation, and deployment. Technical proficiency in modern AI , including comfortable fluency in embeddings, classifiers, ranking systems, and LLM capabilities. Direct experience with LLM-based evaluation frameworks (e.g., "LLM-as-a-judge") and the design of scalable, automated data curation pipelines. Analytical self-sufficiency , with the ability to independently gather and derive actionable insights from complex datasets. Communication & Collaboration The ability to synthesize technical complexity into clear product requirements and executive-level summaries. Cross-functional influence , with a demonstrated ability to drive internal adoption of platform tools and integrate technical signals into diverse product roadmaps. Effective technical partnership skills , maintaining the depth of knowledge required to collaborate closely with ML engineers and architects. Nice to Have Professional background in Data Science or Engineering , providing a hands-on perspective on technical implementation. Active engagement with the ML research community , including staying current with the latest white papers and industry breakthroughs. Benefits: Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave      Pay Transparency: This job posting may span more than one career level. In addition to base s