Build and operate production AI platform services, backend APIs, integrations, and LLM-powered agent workflows. Own development end to end, including design, coding, testing, deployment, observability, troubleshooting, and quality improvement. Develop reusable platform capabilities, evaluate AI application performance, and collaborate with engineering, product, security, data science, and business teams. The role requires Python backend expertise, cloud operations, databases, LLM applications, and agentic software development.

Develops and owns end-to-end machine learning models, from ideation and prototyping through implementation. Responsibilities include building predictive models for credit scoring and recommendation engines, researching model improvements using large datasets, and advancing data science capabilities. Collaborates with analysts and machine learning engineers. Optional experience includes alternate data for credit risk and deep learning or NLP model development.

Develops and owns end-to-end machine learning models, from ideation through implementation. Responsibilities include prototyping credit-scoring and recommendation models, researching improvements using large datasets, and advancing the organization’s data science capabilities. Collaborates closely with analysts and machine learning engineers while applying quantitative, statistical, and business expertise.