At Meta, I have the opportunity to work on cutting-edge projects that push the boundaries of what is possible with machine learning. My expertise has enabled me to drive significant improvements in model performance, reduce training times, and optimize resource utilization.

Key Areas:

Model Optimization: Proven track record of optimizing machine learning models for improved performance, reduced latency, and increased scalability.

Data Pipeline Efficiency: Skilled in designing and implementing efficient data pipelines that minimize data loss, reduce processing times, and improve overall system reliability.

Collaboration: Strong team player with excellent communication skills, able to work effectively with cross-functional teams to drive project success.

● Worked on designed and implementation for systems to enhance the fallback experience for customers during service or network failures in Prime Video. This implementation guarantees uninterrupted access to Prime Video content during outages, effectively mitigating scaling risks from traffic surges during high-velocity events. The enhanced fault tolerance and resilience of Prime Video services instill significant confidence in their availability, ensuring a seamless and reliable viewing experience for users.

● Led the development of a critical ops tool, improving the onboarding process for Prime Video clients. This initiative yielded substantial efficiency gains by implementing a self-service mechanism for clients to test and proceed with onboarding. The streamlined approach significantly reduced engineering efforts, fostering a more seamless and user-friendly onboarding experience for Prime Video clients.

Designed and developed infrastructure to enhance the customer journey for Kindle Unlimited Sign-Up, improving payment processes and increasing subscription purchases. This initiative contributed to a reduction in churn during the purchase process.

# Kindle- IN Demand Generation:

• Work on features and experiments to generate demand for Kindle eBooks in IN market and expanding the experiments world-wide.

• Few of such experiments that converge are ->

● Customer Preferred Payment Option.

● Kindle Unlimited subscription for Kindle devices in IN.

● Ebooks -Cart which enables customers to buy more than one ebooks through single checkout.

● Recommending Payment Method to customer while checkout based on ML-Model trained on 400 odd parameters.

● Kindle Unlimited Subscription

# Worked with Digital payments team -

● Reducing friction for Customers who have the intent to purchase Ebooks.

● Introduce new payments like UPI, etc for Digital Payment.