Marily Nika Portfolio
PhD computer scientist who led AI product work across Google Assistant and Meta, including a Gboard Greek-language typing feature; founder of the AI Product Academy, whose AI Product Management certification has trained 50,000+ people.
What makes it work
A breakdown of the choices that make this portfolio stand out.
A PhD as domain credibility, not just a credential line
Her computer science PhD is directly relevant to evaluating AI product tradeoffs (model capability, data quality, evaluation design) that a purely business-trained PM would need to learn on the job.
A specific, small, named shipped feature alongside big-company brand names
Citing the Gboard Greek-language typing feature — small, concrete, checkable — next to "Google" and "Meta" avoids the common AI-PM portfolio trap of naming only employers without any attributable work product.
Scaling personal expertise into a training program with a stated outcome number
Turning individual AI PM experience into a certification with a specific claimed reach (50,000+ people) is itself a product-management exercise: identifying a gap and shipping a scalable solution to it.
What AI Product Managers can take from this
Specific, actionable tips to apply to your own portfolio — no generic advice.
Name at least one small, specific, checkable feature you shipped, not just the company names on your résumé — specificity separates a real AI PM portfolio from a title list.
If your technical background is directly relevant to your product decisions, connect the two explicitly rather than listing them separately.
If you've built training material or a course from your practitioner experience, that's a legitimate portfolio artifact — it shows you can generalize your knowledge.
More AI Product Manager portfolios
Ready to build your portfolio?
Follow the AI Product Manager roadmap — skills, projects, and timeline to get hired.