Staff Product Manager (Remote)

Weedmaps is a global leader in the cannabis industry, dedicated to transparency, education, and community. The Staff Product Manager will focus on Personalization, ensuring the delivery of tailored experiences for customers by partnering with ML and AI teams to enhance personalization capabilities across the platform.

Responsibilities:

• Define a roadmap that achieves a world-class personalization strategy, delivering relevant and tailored experiences across the Weedmaps platform
• Partner with ML and AI teams to build and scale personalization capabilities, including product recommendations, personalized search ranking, and AI-powered features
• Translate business goals and customer needs into a logically sequenced and optimized product roadmap
• Maintain and prioritize a backlog, ensuring new features and enhancements are validated and clearly specified
• Lead a cross-functional team to implement the personalization vision efficiently, aligning stakeholders across product, engineering, data science, and design
• Monitor adoption, engagement, and revenue impact of personalization features and report on release performance as necessary
• Collaborate with product, program, and engineering leaders across the organization to guide the platform roadmap, pinpointing new opportunities for personalization at scale
• Oversee enterprise-level product planning including identifying new personalization opportunities and incorporating a rolling roadmap of business projects and technology initiatives
• Write complete and detail-oriented product requirements documents, ensuring clear communication to business, design, and development teams
• Engage with customers through a variety of channels and serve as the voice of the customer internally, using insights to inform personalization strategy

Requirements:

• Bachelor's degree or equivalent work experience
• 8+ years of product management experience in a technological industry
• Proven track record of operating at a staff or principal level, driving product strategy across multiple teams or domains
• Deep data background using self-service analytics tooling (Mixpanel, Amplitude, Heap, etc.)
• Experience working with ML/AI teams to build and ship personalization systems, recommendation engines, or intelligent ranking models
• 4+ years experience in consumer-facing online commerce, point-of-sale, or marketplace environments
• 2+ years experience owning a personalization, search, or ML-powered product stack at scale
• Demonstrated ability to influence senior leadership and drive org-wide alignment on complex, ambiguous problems
• Strong strategic aptitude with a proven ability to define a winning product vision and roadmap, particularly in personalization, recommendations, or AI-powered product domains
• Deep customer empathy and experience intuition; demonstrated success building tailored, intelligent user experiences that drive engagement and retention
• Excellent communication and persuasion skills; proven ability to build executive buy-in for bold, long-term bets in emerging AI/ML product spaces
• Strong analytical and quantitative skills with a bias toward data-driven decision making, including comfort with A/B testing, experimentation frameworks, and ML model evaluation
• Ability to translate personalization strategy into detailed, actionable product requirements that bridge business goals and ML/AI capabilities
• High technical fluency; comfortable engaging deeply with ML engineers and data scientists on model tradeoffs, feature pipelines, data infrastructure, and system architecture
• Proven ability to navigate build vs. buy vs. partner decisions for AI/ML capabilities, balancing customer impact with speed to market
• Comfortable operating in ambiguity; able to define structure and drive progress on complex, cross-functional initiatives without a clear playbook
• Strong bias for action with the ability to manage competing priorities across multiple teams in a fast-paced, high-growth environment
• Proven ability to lead and align cross-functional teams — including engineering, data science, design, and marketing — through influence rather than direct authority
• Familiarity with modern AI/ML development workflows, including experience working in agile environments with data science and ML engineering teams