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Design and develop computer vision, machine learning, AI, predictive, classification, recommendation, and LLM-based models. Responsibilities include algorithm selection and optimization, data cleaning, feature engineering, model validation, production deployment, and collaboration with clients and internal teams to turn analytical results into actionable insights.

Designs, develops, validates, and deploys machine learning, computer vision, AI, and LLM-based models. Responsibilities include data cleaning, feature engineering, algorithm optimization, production integration, and collaboration with clients and internal teams to deliver actionable insights. The role requires Python-based modeling, statistical knowledge, SQL, version control, and cloud or on-premise deployment experience.

Leads end-to-end data science and machine learning projects, from client discussions and solution design through production deployment. Designs predictive, classification, computer vision, LLM, and recommendation models; performs data preparation, feature engineering, validation, and optimization. Integrates models into production, contributes to architecture, mentors junior staff, and presents results to technical and business stakeholders. The role also involves technical leadership, client communication, project ownership, and occasional presales or proof-of-concept work.

Lead end-to-end data science and machine learning projects, from client discussions and solution design through production deployment. Design computer vision, predictive, classification, LLM, and recommendation models; optimize algorithms; clean data; engineer features; validate models; and integrate solutions into production. Mentor junior staff, contribute to architecture, define tools and processes, manage projects, and present analytical findings to technical and business stakeholders.