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As a Sr. Data Scientist at CMX, you will lead the development and deployment of cutting-edge Generative AI (GenAI) solutions within one of the largest health-aligned enterprise ecosystems. This role focuses on building scalable, production-grade systems using Python and modern frameworks, with applications such as Retrieval-Augmented Generation (RAG) and intelligent agents. You will work at the intersection of data science, engineering, and MLOps, collaborating with stakeholders to clarify requirements and deliver impactful solutions that enhance patient and consumer experiences.
Job Responsibility:
Design and implement GenAI solutions, including RAG pipelines and agent-based systems, for enterprise-scale applications
Build and optimize backend systems using Python and frameworks like FastAPI, ensuring robust and efficient deployments
Collaborate with data engineering and MLOps teams to integrate models into production workflows
Work consultatively with stakeholders to understand business needs, present results, and guide technical decisions
Contribute to best practices for coding standards, workflow efficiency, and distributed computing
Requirements:
3+ years of coding experience (primarily on Python)
3+ years of experience in backend systems development (FastAPI experience is a plus)
Proven track record of building and deploying GenAI solutions (e.g., RAG pipelines, agent-based systems)
Hands-on experience with GenAI frameworks such as LangChain, LangGraph, or similar
Experience working in cloud environments (GCP, Azure, or AWS)
Strong collaboration skills and ability to thrive in agile team settings
Ability to communicate technical concepts effectively to stakeholders
Master's degree or equivalent work experience in a relevant field
Nice to have:
Experience integrating GenAI solutions and agentic design into enterprise workflows
Exposure to MLOps practices and tools (e.g., Jenkins, Docker)
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