William Mee is a seasoned software engineer with nearly three decades of experience in frontier technologies, most recently pursuing an Executive MBA at UC Berkeley’s Haas School of Business. His career spans pioneering internet services in the late 1990s, nearly a decade at Google on products like Google Maps and Android, roles at Thumbtack and Coda, and critical infrastructure development at Zoox, an Amazon company building purpose-built autonomous vehicles.
Background
William began his career in the late 1990s as an undergraduate in computer science, graduating just as the commercial internet emerged. He joined an early internet service provider, helping major companies connect to the network for the first time during this pivotal shift toward widespread adoption of the “network of networks.”
In 2009, after earning a master’s in computer science from Columbia University and securing back-to-back internships, William joined Google full-time. He spent just under 10 years there until 2019, thriving in its renowned engineering culture amid fascinating systems and creative teams. Leveraging Google’s high internal mobility, he contributed to products including AdWords, Google Maps, and various Android developments, experiencing the company’s massive growth while building diverse technical expertise.
Seeking broader tech experiences beyond Google’s “cathedral-like” environment, William left in 2019 for roles at Thumbtack and Coda. In 2023, drawn to the visible rise of autonomous vehicles in San Francisco and the challenge of hardware-software integration, he joined Zoox as a software engineer. There, he developed the fleet orchestration and dispatch system, akin to air traffic control for robots, optimizing vehicle-passenger matching while factoring in battery levels, routes, charging, and autonomous complexities.
In 2025, while working at Zoox, William prioritized his Executive MBA at Haas, stepping away from industry to focus on business leadership amid rapid tech change. Across nearly 30 years, he has navigated multiple innovation cycles, from internet commercialization to AI-driven autonomy, blending deep technical skills with a drive for broader perspectives.
Core Expertise
William specializes in software engineering for scalable, real-world systems, particularly in fleet management, AI perception, and autonomous robotics. He is known for building mission-critical infrastructure like Zoox’s dispatch systems, which handle dynamic matching in ride-hailing under autonomous constraints, and for his insights into industry challenges from Google-scale products to hardware-integrated vehicles.
Academia
William earned his undergraduate degree in computer science during the internet’s commercial emergence in the late 1990s, gaining early hands-on access as part of his graduating class.
He completed a master’s in computer science at Columbia University, securing consecutive Google internships that led to his full-time role. In 2025, he pursued an Executive MBA at UC Berkeley Haas School of Business, motivated by tech’s relentless change and a desire to develop business acumen beyond pure engineering for leadership in economic and operational contexts.
Balancing the rigorous program with his Zoox role proved intensely demanding, expanding his horizons through diverse peers despite uncertain financial ROI. William values it for irreplaceable experiences and networks, embracing lifelong learning via resources like Andrew Ng’s DeepLearning.AI amid AI’s evolution.
Key Perspectives that William Mee Shares on the Podcast
William asserts self-driving technology is proven, with services like Waymo and Zoox transporting thousands daily despite delays and failures (e.g., Cruise, Apple), marking an irreversible tipping point beyond early hype. He demystifies varied strategies: Zoox’s bidirectional, purpose-built hardware for optimal autonomy versus Tesla’s low-cost cameras or Aurora’s truck retrofits, each a calculated bet on integration, scaling, and safety.
Challenges span technical (spectrum from Level 1 assistance to Level 4 geofenced ops), operational (fleet scaling, teleops at 1: many vehicles), and safety (edge cases via simulation metrics like fault-free km, already 83% safer than humans per Waymo). He envisions mainstream mobility reducing car ownership, boosting freeway capacity, and creating skilled jobs in ops/logistics, urging pragmatism over over-optimism while highlighting rapid user normalization.
A Quote from this Conversation with William Mee
“by the time you take the second ride in an autonomous vehicle, it already becomes something which is almost commonplace and you just accept it”
