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Lead the design and implementation of state-of-the-art machine learning models and algorithms to solve complex business problems. Utilize various techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning, to extract insights from large datasets. Conduct exploratory data analysis to uncover patterns, trends, and relationships in the data. Identify relevant features and variables for model development and feature engineering. Develop data preprocessing, cleansing, and augmentation strategies to improve model performance. Ensure that machine learning models are transparent and interpretable by utilizing explainable AI techniques. Develop methods to interpret model predictions and comprehend model behavior, especially in high-stakes or regulated domains. Lead the development of backend services and infrastructure to support machine learning applications across various platforms and surfaces, ensuring seamless integration with existing systems. Design GPU optimized model pipelines to efficiently process diverse data modalities, including images, vectors, and 3D assets. Design internal AI platforms and frameworks for model inference and deployment and develop highly scalable and resilient systems to efficiently handle large-scale machine learning workloads. Collaborate closely with cross-functional teams of data scientists, software engineers, and product managers to employ innovative architectures and cutting-edge techniques to develop optimized solutions for business problems and offer technical leadership to ensure alignment with organizational goals.
