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At PPRO, we simplify access to local payments - providing a local payments platform that empowers giants like PayPal, Stripe, and Microsoft to connect with billions of consumers worldwide. We are on an ambitious, fast-paced mission to 3x our growth by 2028 - and we’re just getting started. Our magic lies in our team of proud payments nerds. Spanning over 50 nationalities across 10+ global locations, our diverse cultures aren't a checklist; they are the competitive advantage driving our innovation. This is a people-first, high trust environment where you’ll have the autonomy to make a massive impact, own your work end-to-end, and grow through broad exposure, meaningful challenges, and continuous learning. We get things done, challenge respectfully, put the customer first, and recognise that our biggest successes are those we create as a team. If you’re ready to leave your footprint on global commerce, join us. The Purpose: As a Staff Machine Learning Engineer in PPRO's Performance Powerhouse team, you will define the technical vision and architecture for ML-driven payment optimization across the organization. You will move beyond executing well-defined problems to identifying and framing the highest-leverage opportunities—bridging strategy, architecture, and execution across multiple teams. You'll partner deeply with Product, Data, Core Payments, and Platform Engineering to set standards, eliminate systemic bottlenecks, and ensure PPRO's ML capabilities scale with the business. This role is for engineers who have mastered ML and software craft at the senior level and are now ready to multiply their impact through technical leadership, mentorship of senior engineers, and architectural decisions that shape how the Data & ML organization builds and deploys ML systems. You will be the technical authority on ML for payments at PPRO—setting the direction others follow, raising the bar across the discipline, and driving alignment across engineering, product, and data teams.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.
