Top AI & Machine Learning Jobs

The Machine Learning Platform Engineer will design and build scalable ML systems, improve workflows, and work closely with ML teams to enhance infrastructure and developer experience.

Lead product analytics for Spending, driving experimentation, causal measurement, metric frameworks, and dashboards. Partner cross-functionally to surface insights, guide product roadmaps, mentor on experimentation, and ensure analytics drive member engagement and retention.

Lead product-focused trust & safety analytics: design experiments, run causal measurement, build metric frameworks and dashboards, translate member behavior into product recommendations, and partner cross-functionally to drive adoption and impact.

Partner with Growth Product and Engineering to own funnels end-to-end, design and analyze A/B tests, run causal inference and forecasting, build dashboards and self-serve analytics, improve eventing, and translate analyses into product recommendations to drive acquisition, activation, and retention.

Lead product-focused analytics and experimentation for Growth: design and analyze A/B tests, build metrics and dbt data pipelines, apply causal inference and ML, enable self-service analytics, improve funnels and retention, and translate insights into executive recommendations to drive member acquisition, conversion, and long-term value.

Develop and iterate on ML models and training pipelines for risk decisioning. Support offline evaluation and online experiment analysis, write maintainable code, and collaborate with cross-functional partners to deploy and monitor production ML systems, including work on generative AI and sequence-model applications.

Build and deploy transformer and sequential deep learning models using large-scale financial and behavioral data to power personalized growth and marketing experiences. Work cross-functionally to design scalable training, serving, and monitoring infrastructure (batch and real-time), contribute to experimentation and optimization frameworks, and maintain production-grade MLOps systems to improve member engagement and business metrics.