Director, AI & Data Science

DIRECTOR, AI & DATA SCIENCE

Data Engineering & Analytics, AI, and Data Science Full-Time, Salaried Player-Coach Reports to the Co-CEOs

A hands-on director who leads six or seven people, writes production code every week, and solves our most immediate problems first: fully automated moderation and AI customer support.

Company

Seeking.com (Reflex Media)

Location

Remote, anywhere in the USA

Team

Six to seven individual contributors across data engineering, analytics, data science, ML, and MLOps

Education

Master’s degree required. Ph.D. a plus.

Compensation

$180,000 to $230,000 base

Schedule

Collaboration across time zones. Regular working-hour overlap with our Singapore Dev team and partners is required.

Travel

Required for team weeks and quarterly planning in Las Vegas

About the Role

Seeking.com is the world’s largest premium dating platform, founded and led by an MIT alumnus and headquartered in Las Vegas. We are a lean company of about 60 people, so every leader here builds.

You will lead our combined Data Engineering & Analytics, AI, and Data Science team of six to seven individual contributors and report directly to the Co-CEOs. This team is Seeking’s central AI capability: the models, infrastructure, evaluation frameworks, and continuous-learning systems the whole company runs on. Expect about half your time leading and half writing code, building models, and debugging production systems yourself.

Your first mandate is to achieve 100% AI automation of routine user-uploaded content moderation, with accuracy proven superior to our human moderators and at a lower total cost. Next is AI customer support that resolves member tickets end to end. You own both outcomes completely, from policy and data through production results.

Over time, the team will extend AI to fraud prevention, matching, member onboarding and success, marketing, monetization, retention, and product development, in partnership with the leaders who own those areas. Every initiative carries a measurable target, a named owner, and a mechanism for continuous learning. The immediate problems come first, and this role exists to solve them.

This role is for someone who manages a hands-on team today and still ships code. If your recent roles had managers reporting to you, or you plan to delegate the technical work and manage through status meetings, this is the wrong role. If you walk into ambiguity and know exactly what to do, keep reading.

What You Will Do

1. Set the foundation in your first 30 days

• Bring Product, Support, and Operations to one written moderation policy with a single owner. When teams disagree, you run the process that settles it.
• Inventory every production AI system with a named owner, backup, dependencies, and monitoring gaps.
• Trace every upload from receipt through model decision, enforcement, and any human review. Quantify every path that still needs a human, with its root cause, cost, and fix.

2. Prove AI beats our human moderators, then reach 100%

• Test the AI and our moderators on the same held-out cases, with reference decisions set by independent, policy-qualified reviewers. Report missed violations and wrongful rejections separately, with sample sizes and confidence intervals.
• Close every gap: missing coverage, uncertain model outputs, system failures, unenforced decisions, and duplicate human review. Expand automation in controlled stages, each with a tested rollback.

3. Build systems that keep getting better

• Every production system improves through verified feedback, independent evaluation, and controlled releases. Run a monthly learning cycle in which a new model ships only when it beats production on the same independent test.
• Version every dataset, policy, prompt, and model so every gain can be proven and every change can be rolled back.

4. Run production AI like a business

• Give every production AI system monitoring, alerts to a named owner, documented recovery, and regular failure drills.
• Report results in business terms: quality, cost per outcome, revenue, efficiency, and member experience, with savings reconciled with Finance. Keep one executive dashboard and run a weekly review with the Co-CEOs.

5. Automate support, then partner across Seeking

• Own AI customer support end to end: agents that resolve tickets and execute approved actions, such as subscription changes and eligible refunds, held to the sa…