Staff Software Engineer (ML) in London

You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we're behind many of the digital experiences you use every day. Whether you want to book a holiday, order food, renew a subscription, or check out online, there's a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale. com, our software engineers develop the next-generation financial technologies that empower merchants to optimize acceptance rates, combat fraud and unlock seamless customer experiences. As a Staff Software Engineer within our Payments Performance pillar, you will step into a critical role of strategic technical leadership. We are looking for someone with a background building robust, automated experimentation or decision engines at a global scale. How you'll make an impactDrive the long-term technical direction and strategy for the Experimentation and Optimisation platform, looking beyond immediate requirements to ensure our solutions are built for impact and scale. Collaborate cross-functionally with Data Science, Platform and ML Engineering teams to shape what we build, not just how. Participate, translate, run and execute the collection of requirements and architecture/design initiatives into clear, actionable engineering roadmaps. Extensive, hands-on experience in building, operating and scaling complex, cloud-based distributed systems (we use mainly AWS).Excellent programming skills in Go (Golang), with a deep understanding of concurrent, memory-efficient, and low-latency backend architectures. A strong engineering background with a proven track record of implementing, owning, and scaling experimentation systems, feature-flagging infrastructures, or similar data-intensive backend systems. A proven ability to raise the bar for engineering standards through effective coaching, mentorship, and a relentless drive for platform improvement. A detail-oriented and data-driven approach to building infrastructure solutions where accuracy, thoroughness, and low latency are absolutely critical. Bonus: experience with implementing solutions for adaptive experimentation ML (contextual bandits, Bayesian optimization or RL-based allocation)Additional InformationBring all of you to workWe create the conditions for high performers to thrive, through real ownership, fewer blockers, and work that makes a difference from day one. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection.