The Challenge
LinkedIn owns one of the world's most valuable email channels—reaching millions daily. You'll architect the AI systems that decide what content each member sees, balancing engagement, relevance, and economic opportunity at massive scale.
Your Mission
Map the current email content AI landscape: audit existing personalization, content selection, and ranking systems; identify gaps and opportunities
Define the north star vision and success metrics for AI-powered email content—align stakeholders across PM, Engineering, Data Science, and Marketing
Prioritize and scope the first AI-powered initiative (content generation, ranking, or personalization) with a clear MVP and go/no-go criteria
Build deep user understanding through qualitative research with members and internal stakeholders on email engagement patterns and unmet needs
Ship and iterate on first AI-powered capability; measure impact on open rates, click-through rates, DAU retention, and member satisfaction
Establish scalable experimentation framework and guardrails for testing AI-generated vs. curated content
Define governance model for responsible AI in email (bias, privacy, legal, brand voice) and document for cross-functional alignment
Build product roadmap for next 12 months with 3+ prioritized AI initiatives; secure engineering and data science commitment
KPIs You'll Own
Email Open Rate
Percentage of recipients who open emails; primary driver of engagement and member value.
Click-Through Rate (CTR)
Percentage of email opens that result in a click; measures content relevance and call-to-action effectiveness.
Member Lifetime Value (LTV) from Email
Long-term DAU retention and economic value attributable to email engagement; core business KPI.
Email Unsubscribe Rate
Percentage of members opting out; inverse indicator of relevance and over-personalization risk.
AI Content Quality Score
Internal or external rating of generated/ranked content (brand voice, accuracy, relevance); ensures responsible AI deployment.
Tools & Stack
Your Team
Your Manager
Not specified; likely Senior Director or VP of Product
Current Team
Engineering, Data Science, Design, Editorial, Marketing, PMM, Legal, Privacy teams (cross-functional matrix)
New strategic initiative or backfill; core growth function for LinkedIn
The Package
Salary
$220K-$280K base
Variable
Estimated 20-30% annual bonus
Equity
Significant stock package (estimated $300K-$600K vesting over 4 years)
Remote
Hybrid (Mountain View or San Francisco office; on-site select days per business needs)
Benefits & Perks
Company Intelligence
LinkedIn is the world's largest professional network (900M+ members) with deep influence on how professionals discover jobs, build skills, and drive economic opportunity. Part of Microsoft (acquired 2016), LinkedIn operates at massive scale with sophisticated AI/ML infrastructure. The platform's email ecosystem is a critical retention and engagement lever.
Founded
2003
Team Size
19,000+
Funding
Acquired by Microsoft for $26.2B (2016)
Customers
Individuals, recruiters, enterprises, educators globally
Culture
Trust, care, inclusion, and fun; employee-centric with focus on growth and economic opportunity
Is This Role For You?
- You've shipped AI/ML-powered product features (personalization, content ranking, or generation) and can speak to tradeoffs between relevance, scale, and responsible AI
- You're comfortable operating in high-ambiguity environments and can define problems from first principles; you thrive owning full-stack product (strategy → execution → iteration)
- You have experience working with data scientists and engineers to scope and ship ML systems; you can read and interpret metrics with rigor
- You're energized by massive scale (millions of users) and long-term impact; you think in terms of member lifetime value, not just vanity metrics
- You need remote-first flexibility; this role is explicitly hybrid in the Bay Area with on-site days required
- You prefer waterfall planning and waiting for perfect information; LinkedIn moves fast and requires rapid experimentation and iteration
- You lack hands-on experience shipping product or working cross-functionally with eng/data; this is a hands-on, full-stack PM role
Interview Process
Recruiter Screen
Alignment on role, background, and expectations; ~30 min
Hiring Manager Conversation
Deep dive on product strategy, past AI/ML work, team collaboration; ~60 min
PM Case Study / Whiteboard
Design an AI-powered email personalization or content ranking system; define metrics and roadmap; ~90 min
Cross-Functional Loop
Meetings with Engineering, Data Science, Design, and Marketing stakeholders; ~120 min total
Execs / Final Round
Leadership alignment conversation on vision, strategy, and org fit; ~60 min
Interested in this role?
Apply now and hear back within days, not weeks.
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