Top AI & Machine Learning Jobs

Lead strategy, roadmap, and execution for AI-powered fintech products. Build and ship ML/LLM-driven features (copilots, chatbots, recommendations), drive product-led growth initiatives, automate customer support, ensure responsible AI and compliance, launch across regions, and mentor other product managers.

Lead strategy, roadmap, and execution for AI/LLM-powered growth products in fintech. Build end-to-end AI features (copilots, chatbots, recommendations), drive PLG experiments, partner cross-functionally, ensure responsible AI and compliance, launch multi-region products, and mentor other PMs.

Partner with Product and Engineering to analyze large datasets, run experiments, build statistical models, define product metrics, forecast outcomes, and deliver insights that drive product strategy and roadmap decisions.

Lead design and build of high-performance distributed data infrastructure and AI enablement platforms. Optimize systems internals and JVM performance, implement lakehouse and real-time streaming, develop scalable vector indexing and AI knowledge platform, own SDLC for petabyte-scale systems across global regions, drive engineering best practices, and mentor mid-level engineers.

Lead modelling and analysis roadmap for FX products: forecast and monitor FX volatility, optimise trade execution with statistical/ML models, run customer and profitability analyses, and partner with product, trading, risk, and engineering to translate insights into trading and product decisions.

Lead product strategy and delivery for AI-focused developer tools that simplify integration with Airwallex. Own toolkits, SDKs, APIs, documentation, and community advocacy; collaborate with engineering and cross-functional teams to drive adoption, analyze data, and balance user needs with commercial outcomes.

Technical lead for Growth Analytics: partner with Growth/Marketing/Sales to identify opportunities, design experiments and statistical models, build scalable measurement frameworks, mentor junior data scientists, translate business questions into analytic solutions, and communicate insights to drive acquisition, activation, retention, and reactivation.