Translate complex business questions into measurable modeling problems and deploy AI-enhanced solutions into production. Build and maintain demand forecasting models, optimization services, and APIs while collaborating with data engineering teams.
You will build machine learning models and AI-powered solutions, managing the end-to-end lifecycle from data extraction to real-time deployment. Additionally, you will design and develop production-ready LLM applications, including RAG systems and multi-agent architectures.
You will develop and scale AI solutions to extract and structure data from complex, unstructured visual and textual documents like floor plans. Additionally, you will integrate this intelligence into recommendation funnels using tools such as PostGIS and vector databases.
Design, build, and deploy enterprise-grade GenAI and agentic workflows for complex financial services, including exception classification and root-cause analysis. Collaborate with cross-functional teams to integrate AI applications with enterprise APIs and data sources while ensuring production-grade observability and performance.
The role involves designing, building, and deploying scalable AI-enhanced applications using Python and large language models. You will be responsible for backend orchestration, system integration, and ensuring secure, high-performance API architectures.
Build, validate, and deploy statistical and machine learning models including anomaly detection and generative AI. Collaborate with cross-functional teams to translate strategic business questions into scalable, production-ready data solutions.
