Senior Product Manager, ML Signals

📋 Description

• Develop the long-term strategy for foundational "content understanding" signals, which includes interest-based tagging (topicality), content maturity, and quality scores utilized across the platform.

• Serve as the key liaison between the MLE team and downstream stakeholders (such as Feed, Ads, Search, and Safety). Facilitate the integration of ML signals to enhance personalization and brand safety.

• Create standardized definitions and success metrics for content quality and utility, ensuring a uniform comprehension of "high quality" across various product surfaces.

• Direct the strategy for acquiring high-quality training data, incorporating "Human-in-the-Loop" (HITL) workflows and advanced automated evaluation methods (for instance, employing Large Language Models to aid in data labeling).

• Collaborate with Data Science and MLE teams to assess signal health, coverage, and accuracy (Precision/Recall), translating technical performance into business outcomes (such as retention, engagement, or revenue).

• Navigate intricate trade-offs among Policy, Engineering, and Product teams to ensure signals fulfill both user safety standards and product growth objectives.

⛳️ Requirements

• Over 5 years of experience in Product Management, specifically focused on Machine Learning, NLP, or Platform products.

• A proven track record of delivering high-impact products that yield measurable business outcomes.

• Ability to autonomously manage roadmaps, leading complex services from initial vision through execution and scaling.

• Strategic foresight, with the capability to establish clear goals and success metrics that align with broader organizational aims.

• Profound understanding of the ML lifecycle, including data collection, feature engineering, model evaluation, and deployment.

• Technical expertise in modern AI, including proficiency with embeddings, classifiers, ranking systems, and LLM capabilities.

• Hands-on experience with LLM-based evaluation frameworks (such as "LLM-as-a-judge") and designing scalable, automated data curation pipelines.

• Analytical independence, with the capacity to gather and interpret actionable insights from complex datasets on your own.

• Ability to distill technical complexities into clear product requirements and executive-level summaries.

• Cross-functional influence demonstrated through the ability to promote internal adoption of platform tools and integrate technical signals into various product roadmaps.

• Strong technical collaboration skills, maintaining the depth of knowledge necessary to closely work with ML engineers and architects.

🏝️ Benefits

• Comprehensive Healthcare Benefits and Income Replacement Programs

• 401k with Employer Match

• Global Benefit programs that accommodate 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