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Shashank
Kapadia
Staff Machine Learning Engineer
Walmart Global Tech
Shashank Kapadia is a machine learning engineering leader specializing in large-scale AI solutions that drive measurable improvements in user engagement and business outcomes. With over a decade of hands-on experience at global organizations like Walmart, Randstad, and Monster Worldwide, he has pioneered cutting-edge ML solutions optimizing revenue, boosting engagement, and streamlining decision-making. Shashank’s approach balances technical rigor with ethical responsibility. He champions fairness, transparency, and real-world relevance, ensuring solutions serve both the enterprise and the broader community. An active mentor and thought leader, he has spoken at global conferences, judged and mentored hackathons, authored widely-read articles on NLP, and co-authored published research guiding teams to award-winning results. A valedictorian graduate in Operations Research from Northeastern University, Shashank continues to push the boundaries of ML innovation. His work exemplifies a seamless fusion of cutting-edge techniques, high-level strategy, and values-driven execution—advancing technology that’s as impactful as it is responsible.
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15 April 2025 16:30 - 17:00
Panel | What breaks when GenAI scales: Latency, cost, and reliability in the real world
As GenAI adoption grows, the underlying infrastructure is under constant strain. Latency spikes, unpredictable traffic, rising inference costs, and brittle retrieval layers often emerge long after a system looks stable in testing. This session explores how engineering teams are redesigning serving layers, data pipelines, and performance workflows to keep GenAI systems fast, affordable, and reliable at scale. Key takeaways: → How teams reduce latency under real-world load → The cost impact of routing, batching, and caching decisions → Where retrieval layers and vector search introduce scaling limits → Architectural choices that improve reliability as usage grows