Growth-Focused Full-Stack Engineer (ML & Experiments)

Stripe Elements

Singapore

On-site

SGD 60,000 - 110,000

Full time

7 days ago
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Job summary

Stripe Elements in Singapore is seeking a growth-focused full-stack engineer to design and ship experiments across stripe.com and related dashboards. You will work with data scientists and product managers to translate growth hypotheses into technical implementations and measurable outcomes.

You'll build scalable backend APIs in Ruby, power responsive frontend experiences with React and JavaScript, and contribute to ML-driven recommendations and growth experiments that impact key metrics.

Qualifications

  • 2–5 years of software engineering experience
  • Strong collaboration skills across workstreams
  • Ability to work autonomously with ownership
  • Deep care for user experiences and outcomes
  • Experience delivering small to medium projects independently or with guidance

Responsibilities

  • Build and maintain scalable systems and customer experiences for Stripe products
  • Develop backend APIs in Ruby powering frontend experiences with React/JS/CSS
  • Implement ML-driven recommendations and experimentation frameworks
  • Translate growth hypotheses into technical implementations and A/B tests
  • Contribute to shared platforms enabling rapid experimentation across growth initiatives
  • Debug production issues across the full stack and participate in on-call rotations
  • Write maintainable, well-tested code following team conventions

Skills

Software engineering
Collaboration
Autonomy
User experience

Tools

Ruby
React
JavaScript
CSS

Job description

Stripe Elements in Singapore is seeking a growth-focused full-stack engineer to design and ship experiments across stripe.com and related dashboards. You will work with data scientists and product managers to translate growth hypotheses into technical implementations and measurable outcomes.

You'll build scalable backend APIs in Ruby, power responsive frontend experiences with React and JavaScript, and contribute to ML-driven recommendations and growth experiments that impact key metrics.

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