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Author:

Saket Agarwal

Senior Director and Head of Engineering
Uber

Saket Agarwal is a seasoned product and engineering leader with nearly 20 years of experience across top-tier technology companies. Currently, as the Senior Director and Head of Engineering at Uber, he manages a team of full-stack software and machine learning engineers/scientists, overseeing the development of customer support & engagement platforms. His work at Uber involves leading a global team to deliver innovative AI-driven solutions that enhance customer interactions across diverse user groups, while partnering across teams at Uber to shape the vision in AI/ML.

Before joining Uber, Saket played a pivotal role at Amazon Web Services (AWS) as the Director of Software Engineering, where he led teams of over 200 engineers in creating Amazon Connect, a cutting-edge AI-powered contact center solution. His career also includes significant contributions to Amazon's Alexa conversational intelligence platform, Adobe's Correspondence Management solution, D. E. Shaw & Co., and IBM, where he honed his expertise in software development, digital customer engagement products, and AI applications. Saket’s leadership style is rooted in humility, technical excellence, and a relentless drive for operational efficiency, making him a key figure in the AI and customer service technology landscape.

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Saket Agarwal

Senior Director and Head of Engineering
Uber

Saket Agarwal is a seasoned product and engineering leader with nearly 20 years of experience across top-tier technology companies. Currently, as the Senior Director and Head of Engineering at Uber, he manages a team of full-stack software and machine learning engineers/scientists, overseeing the development of customer support & engagement platforms. His work at Uber involves leading a global team to deliver innovative AI-driven solutions that enhance customer interactions across diverse user groups, while partnering across teams at Uber to shape the vision in AI/ML.

Before joining Uber, Saket played a pivotal role at Amazon Web Services (AWS) as the Director of Software Engineering, where he led teams of over 200 engineers in creating Amazon Connect, a cutting-edge AI-powered contact center solution. His career also includes significant contributions to Amazon's Alexa conversational intelligence platform, Adobe's Correspondence Management solution, D. E. Shaw & Co., and IBM, where he honed his expertise in software development, digital customer engagement products, and AI applications. Saket’s leadership style is rooted in humility, technical excellence, and a relentless drive for operational efficiency, making him a key figure in the AI and customer service technology landscape.

Author:

Arun Nandi

Senior Director and Head of Data & Analytics
Unilever

Arun is a visionary AI and Analytics expert recognized as one of the Top 100 Influential AI & Analytics leaders. He is the Head of Data & Analytics at Unilever today. With over 15 years of experience driving analytics-driven value in organizations, he has built AI practices from the ground up on several occasions. Arun advocates the adoption of AI to overcome enterprise-wide challenges and create growth. Beyond his professional achievements, Arun loves to travel, having explored over 40 countries and is passionate about adventure motorbiking.

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Arun Nandi

Senior Director and Head of Data & Analytics
Unilever

Arun is a visionary AI and Analytics expert recognized as one of the Top 100 Influential AI & Analytics leaders. He is the Head of Data & Analytics at Unilever today. With over 15 years of experience driving analytics-driven value in organizations, he has built AI practices from the ground up on several occasions. Arun advocates the adoption of AI to overcome enterprise-wide challenges and create growth. Beyond his professional achievements, Arun loves to travel, having explored over 40 countries and is passionate about adventure motorbiking.

The journey from taking a foundation model (FM) from experimentation to production is filled with choices, decisions, and pitfalls that can increase undifferentiated heavylifting and delay time-to-market. In this session, learn how purpose built capabilities in Amazon SageMaker can help ML practitioners pre-train, evaluate, and fine-tune FMs with advanced techniques, and deploy FMs with fine-grain controls for generative AI use cases that have stringent requirements on accuracy, latency, and cost. Join us to learn how to simplify the generative AI journey, follow best practices, save time and cost, and shorten time-to-market.

Author:

Ankur Mehrotra

Director and GM, Amazon SageMaker
AWS

Ankur is a GM at AWS Machine Learning and leads foundational SageMaker services such as SageMaker Studio, Notebooks, Training, Inference, Feature Store, MLOps, etc. Before SageMaker, he led AI services for personalization, forecasting, healthcare & life sciences, edge AI devices and SDKs, as well as thought leadership programs such as AWS DeepRacer. Ankur has worked at Amazon for over 15 years. Before joining AWS, he spent several years in Amazon’s Consumer organization, where he led the development of automated marketing/advertising systems, as well as automated pricing systems.

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Ankur Mehrotra

Director and GM, Amazon SageMaker
AWS

Ankur is a GM at AWS Machine Learning and leads foundational SageMaker services such as SageMaker Studio, Notebooks, Training, Inference, Feature Store, MLOps, etc. Before SageMaker, he led AI services for personalization, forecasting, healthcare & life sciences, edge AI devices and SDKs, as well as thought leadership programs such as AWS DeepRacer. Ankur has worked at Amazon for over 15 years. Before joining AWS, he spent several years in Amazon’s Consumer organization, where he led the development of automated marketing/advertising systems, as well as automated pricing systems.

Innovation Showcase Applicant Pack - Animal Health USA 2024