Top AI & Machine Learning Jobs

Lead design, build, and productionize large-scale ML systems (including RL-based recommenders). Collaborate with Product and Data Science to create data pipelines, cloud architectures, CI/CD, model retraining, monitoring, and Responsible/Explainable AI practices. Mentor and lead teams to deliver performant, resilient ML applications across web, mobile, and email.

Lead AI and automation product strategy for Finance transformation: define and launch AI features and automated workflows, manage model lifecycle with cross-functional teams, ensure responsible AI and compliance, and use AI metrics to iterate and deliver measurable operational leverage.

Lead and deliver large-scale AI/ML programs and the next-generation Generative AI platform. Build and grow a world-class TPM discipline, manage cross-functional delivery, mitigate technical risk, and drive execution across product, engineering, design, and data science to achieve business impact in regulated environments.

Lead development of valuations and credit models for Business Cards & Payments. Partner with cross-functional teams to design, train, validate, monitor, and implement ML solutions using Python, Spark, H2O, and cloud infrastructure. Translate technical work into business impact and support tooling and analytics for credit programs.

Drive intake, prioritization, and refinement of early-stage GenAI use cases for Card products. Break down epics into features and user stories, define acceptance criteria and MVPs, prioritize roadmaps using data, and collaborate with designers, engineers, data scientists, and stakeholders to deliver customer-focused AI-driven product experiences in an agile environment.

Design, build, validate, and deploy machine learning models for Card Finance forecasting. Partner with cross-functional teams to develop a scalable forecasting ecosystem using Python, cloud platforms, and modern data tools, translating technical work into business outcomes.

Build and deploy forecasting and machine learning models for Card Finance, partnering with engineers and product managers. Design, train, evaluate, validate, and implement models using a modern data stack (Python, Snowflake, OneLake, AWS, Spark, H2O) and translate technical results into business decisions.

Lead ML Engineer for Finance Tech to design, build, deploy, and maintain AI/ML systems (including LLMs and RAG). Partner cross-functionally to create production data pipelines, model evaluation, governance, observability, and responsible AI practices while contributing technical vision and scaling AI infrastructure.

Build and deploy forecasting and machine learning models across design, training, evaluation, validation, and implementation. Partner with engineers and product managers to deliver data-driven products, using Python, cloud and big-data tools to analyze large numeric and textual datasets and translate technical results into business impact.

The role involves partnering with data scientists and engineers to develop machine learning models, evaluate model risk in fraud detection, and translate complex data insights into business goals.