Multithread effectively and personalize outreach to convert deals faster
Elevate social presence and drive business growth from social media
Identify and prioritize high-intent leads, and improve sales effectiveness
Find and connect with ICP attendees, and improve event outcomes
Navaneeth Seshadri is a distinguished product leader with extensive experience in Artificial Intelligence (AI), Machine Learning (ML), and MLOps. Currently serving as a Staff Product Manager at Google AI, he focuses on building and scaling cutting-edge AI platforms and infrastructure. Navaneeth is passionate about driving product strategy, developing innovative solutions for complex technical challenges, and translating advanced AI capabilities into tangible user benefits and business impact. His expertise encompasses areas like large language models (LLMs), generative AI, responsible AI, and cloud-native AI solutions. He has a strong track record of leading cross-functional teams to deliver high-impact products in fast-paced environments, consistently demonstrating a deep understanding of both the technical intricacies and the market needs within the AI domain.
Navaneeth Seshadri's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Spearheads product strategy and development for key AI/ML platforms and tools within Google AI, contributing to advancements in areas like generative AI and MLOps infrastructure, impacting millions of users and developers.
Actively contributes to the AI and MLOps community through insightful articles (e.g., on Medium) and potentially speaking engagements, sharing expertise on building, deploying, and managing machine learning systems at scale.
Prior to Google, Navaneeth held significant product roles at companies like Baseten and other AI-focused ventures, where he was instrumental in shaping product roadmaps, launching successful ML-powered features, and fostering product-led growth.
Demonstrates a commitment to developing and deploying AI responsibly, incorporating ethical considerations and fairness into the product development lifecycle for AI systems.
Boston University - Year 2009
DOEACC - Year 2000
Bangalore University - Year 1999
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