Stripe is hiring a Staff Product Manager, ML Foundations and GenAI in 8212 ML Foundations — Seattle, San Francisco, New York, US - Remote. The overview below is synthesized from the employer posting on stripe.com: factual requirements and scope are preserved, but prose is rewritten with editorial context. Verify details and apply via the employer link.
Who we are
About Stripe
Company context from the listing:
Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities.
About the team
Company context from the listing:
You will be joining Stripe’s ML Foundations and Gen AI team to incubate new ML applications and improve our ML capabilities across Stripe. Our team is responsible for unlocking novel ML and LLM techniques and applications across Stripe’s product suite to drive business outcomes, as well as providing infrastructure, tooling and support for ML teams.
What you’ll do
Day-to-day scope for the Staff Product Manager, ML Foundations and GenAI as described in the posting:
As a senior product leader, you will lead a cross-functional team to define, incubate and scale new ML/AI applications across Stripe’s product suite, and drive our strategy and roadmap for ML/AI infrastructure powering all of Stripe’s teams. You will work closely with product leaders across business units to define and deliver on an AI-centric product strategy, launching new applications that drive incremental business outcomes.
Responsibilities
Day-to-day scope for the Staff Product Manager, ML Foundations and GenAI as described in the posting:
- Develop and execute on the Stripe-wide strategy for new ML/AI applications across our product suite
- Evaluate and align on areas of investment for ML/AI applications in collaboration with product leaders across the company
- Work with cross-functional teams to execute on the roadmap and launch successful new ML/AI applications
- Communicate clearly and crisply with leadership stakeholders and drive alignment across multiple teams
- Develop and execute on a strategy for advancing Stripe’s ML/AI infrastructure and tooling
Who you are
Experience and skills the team lists as required:
We’re looking for someone who meets the requirements below, and has a passion for AI to be considered for the role. If you meet these requirements, you are encouraged to apply.
Minimum requirements
Experience and skills the team lists as required:
- 7+ years of experience delivering highly successful and innovative software products which are ML powered
Solid understanding of ML and applied AI tech stacks
Demonstrated ability to influence company level strategy and work with business leaders to execute on the transformation
You push the pace. You take blame and pass the praise. People love working with you.
Proven ability to lead teams and work cross-functionally in a highly collaborative environment.
Ability to analyze and use quantitative and qualitative data to inform decisions.
A deep understanding and empathy for consumer and business users — you love building products that make our customers feel joy, delight and trust.
Relentlessly drives product quality
Capable of working on both 1P and 3P products
Build a standout application
For the Staff Product Manager, ML Foundations and GenAI at Stripe, reviewers look for concise evidence over buzzwords. Mirror the language of the posting sparingly, quantify support or delivery outcomes, and show how you handled ambiguity, time-zone collaboration and user empathy. Keep your resume to impact, keep your cover note to one page, and link to artifacts — tickets resolved, docs shipped, dashboards owned — that prove you can operate in a fast-moving Web3 team. Prepare to discuss a time you turned a confusing user report into a clear fix and how you measure quality in support and operations.
Web3 hiring values reliability: on-time follow-through, clear writing, and a track record of improving runbooks and tooling. Treat the application as a work sample. For interviews, be ready to walk through how you prioritize across time zones, handle a difficult user, and decide when to escalate versus resolve directly. Show how you document decisions so the next teammate benefits.
In a distributed Web3 org, trust builds through written clarity. Use the cover note to demonstrate it.