Key Skills: NLP, Statistical Modelling, Machine Learning, Deep Learning, Agentic AIRoles and Responsibilities:Design and run AI experiments to validate NLP and deep learning use cases, assess model/feature effectiveness, and measure impact.Lead iterative AI product development using hypothesis-driven experimentation, rapid prototyping, pilots/POCs, and data-backed decision making.Own end-to-end ML lifecycle activities including development, validation, deployment, and monitoring in production environments.Partner with engineering and platform teams on architecture discussions, build-vs-buy decisions, and operationalization of ML concepts.Provide senior technical guidance and influence product, engineering, and architecture stakeholders without formal authority.Skills Required:13+ years of experience in AI/digital product development, analytics, or data-driven platform rolesStatistical modelling, probability/statistics foundations, and classical machine learning algorithms.Machine learning and NLP expertise, including deep learning approaches for applied use cases.Advanced proficiency in Python and SQL for experimentation, analysis, and model development.Hands-on ML tooling and lifecycle ownership using scikit-learn, PyTorch and/or TensorFlow, including validation, deployment, and monitoring.Good to Have:Agentic AI experience for building autonomous or tool-using AI workflows.Education: Any Graduation, Any Post GraduationRole: Automation Architect,Industry Type: IT Services & Consulting,Department: Engineering - Software & QA,Employment Type: Full Time, PermanentRole Category: Software DevelopmentEducationUG: Any GraduatePG: Any Postgraduate