Master's or PhD in Computer Science, Mathematics, Statistics, or related field. 12+ Years of experience required relevant to Job Profile. Strong foundation in mathematics, including linear algebra, probability, statistics, and optimization. Proven analytical thinking and problem-solving capabilities. Extensive hands-on experience with Python and PyTorch for building and training ML/DL models. Deep understanding of supervised, unsupervised, and reinforcement learning techniques. Experience with model evaluation, tuning, and deployment in cloud environments (AWS, Azure, GCP). Familiarity with MLOps practices and tools (e.g., MLflow, Kubeflow, Docker, CI/CD pipelines). Strong communication and leadership skills to influence stakeholders and drive adoption.
