Senior Product Manager for Applied AI within Google Cloud, focusing on enterprise-grade products like Healthcare APIs and Risk AI models. The role involves defining strategy, roadmaps, and features for AI/ML products, collaborating with data science teams on model quality, and managing relationships with global banks and healthcare organizations. Requires experience in launching AI/ML products, particularly in Generative AI and large models, with a focus on balancing model quality and cost.

This role involves designing and implementing machine learning solutions for enterprise customers on Google Cloud, acting as a trusted technical advisor, and coaching customers on production ML systems. It requires experience with ML solutions, cloud enterprise solutions, and coding in general-purpose languages, with a preference for recommendation engines, data pipelines, and deep learning frameworks.

Senior Staff Software Engineer role at Google, focusing on Search Intelligence. The role involves technical leadership, designing, developing, and enhancing large-scale software solutions, collaborating with AI/ML researchers and Product Managers, and ensuring the reliability and scalability of Search Intelligence features for the Indian market. Requires 8 years of software development experience and experience in technical leadership.

Staff Software Engineer at Google, focusing on Search Intelligence. The role involves designing, developing, and deploying software solutions to improve the quality of AI-generated content within Google Search. This includes implementing and experimenting with AI/ML models, analyzing performance, and managing open-ended problems in large-scale systems. The position requires experience in AI platform and ML infrastructure, with a focus on improving AI-generated content quality and system health.

This role is for a Data Science Manager to lead a team in India focused on AI/ML initiatives for People Operations. The manager will provide technical leadership, oversee the development and deployment of AI/ML models (including NLP and predictive models), and bridge the gap between business needs and technical execution. The role involves hiring, mentoring, and managing the data science pod, driving technical architecture, and advocating for AI transformation within the organization.