Shreesha Jagadeesh - RecSys at Scale, Leadership and Retail Personalisation

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The NeuralPod

Chris Coyne

16 episodes

3 days ago

The NeuralPod, by NeuralRec.ai The NeuralPod is all about deep diving into technical machine learning topics and showing its real-world impact, bridging the gap between AI-first companies and adoption. We chat with subject matter experts across reinforcement learning, recommender systems, deep learning and generative AI. As well as chatting with business leaders, VCs, operations and strategy experts. Who are NeuralRec.ai? NeuralRec is a recruitment staffing agency. We build niche ML teams and represent some of the globe's best ML talent.

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Technology

Business

Shreesha Jagadeesh - RecSys at Scale, Leadership and Retail Personalisation

The NeuralPod

1 hour 17 minutes

4 months ago

Shreesha Jagadeesh - RecSys at Scale, Leadership and Retail Personalisation

The NeuralPod welcomes Shreesha Jagadeesh, Associate Director of Applied Machine Learning at Best Buy, for an insightful conversation.

Shreesha shares her extensive career journey, from his early days in biomedical diagnostics to her current role at Best Buy. The discussion delves into machine learning techniques in retail, the evolution of recommendation systems, and the technical challenges of personalisation at scale. They also explore his contributions to HR tech at Amazon and his innovative paper on homepage personalisation using XGBoost, soon to be published at RecSys.

Additionally, Shreesha offers valuable advice on leadership, career growth, and navigating the competitive field of machine learning. Get ready for an episode packed with expert insights and practical tips for aspiring AI professionals.

00:00 Introduction and Guest Background
01:48 Career Journey: From Academia to Industry
03:34 Transition to Software and Data Science
04:19 Consulting and Managerial Roles
07:09 Joining Amazon and HR Tech
09:35 Advising a Startup in India
11:19 Joining Best Buy and Recommender Systems
12:46 Challenges in Retail Personalisation
28:28 Implementing XGBoost for Homepage Personalisation
40:01 Top-Down and Bottom-Up Approaches in AI
40:57 Challenges in Implementing Recommender Systems
42:20 Understanding Business Objectives in AB Testing
44:36 Experimentation and Value Demonstration
46:20 Representation Learning in Machine Learning
51:03 Leadership Principles in AI
58:08 Hiring and Team Building in AI
01:02:43 Future of Recommender Systems and Generative AI
01:03:00 Upcoming Book on Recommender Systems
01:10:21 AI Tools for Productivity
01:16:20 Conclusion and Final Thoughts

References:

Multi stage recommender systems blog
https://eugeneyan.com/writing/system-design-for-discovery/

Hidden technical debt in machine learning
https://papers.nips.cc/paper_files/paper/2015/hash/86df7dcfd896fcaf2674f757a2463eba-Abstract.html

HSTU paper
https://github.com/meta-recsys/generative-recommenders/blob/main/README.md