Kyle Hicks

About Kyle Hicks

Professional Summary: AI / ML Capacity and Strategic Planner. Experience in process improvement, operations strategy, automation and managing high performing teams. Strong in program management, problem solving, optimization and effective communication.Main interests in AI / ML Infrastructure, Systems Administration, Configuration Automation, DevOps, Continuous Integration/ Deployment, Virtualization.Skills and technologies: TensorFlow, MCP Servers, VMware, GIT, C#, Powershell, Active Directory, Azure, PDQ, Splunk, Javascript, Herkou, PythonEducational Summary: MBA from Tepper School at Carnegie Mellon. MS Chem E from MIT and BS Eng from Polytechnic Institute of NYU.

Experience

1. Senior Technical Program Manager

   Google

   Nov 2020 — Present · Seattle, WA, US

   Strategic Capacity & Forecasting: Architected and implemented an organization-wide capacity forecasting framework that integrated ML workload patterns and historical data, reducing allocation lead times by 60% and enabling accurate prediction of in compute requirements (TPU, CPU, GPU) for the Ads Org.ML Infrastructure Efficiency & Optimization: Drove critical programs that improved ML (TPU and CPU) inventory efficiency by 20% company-wide. Additionally, designed optimized configurations for LLM and image generation bulk inference, improving resource utilization by 15% and accelerating research iteration cycles.Technical Automation & Program Leadership: Led a 15-SWE engineering team to develop, test, and deploy a fully productionized system to manage a $billions+ full capacity footprint. Personally prototyped the initial solution using Python, SQL, and GoLang, which resulted in a 40% reduction in operational handle-time for capacity delivery.Stakeholder Management & Go-to-Market Velocity: Established and maintained critical relationships with over 300 AI research teams and stakeholders to align compute requirements, constraints, and timelines, resulting in a 25% increase in model team experimentation velocity and faster productization.Major Cost Avoidance: Designed and implemented a safety-stock sharing model between heterogeneous pools of Cloud capacity, resulting in in Capex/Opex inventory cost savings through greater inventory fungibility and effective process centralization.

Education

• Massachusetts Institute of Technology

  Masters of Science, Chemical Engineering (Practice)

  2010 — 2012

• New York University - Polytechnic School of Engineering

  Bachelors of Science, Chemical and Biomolecular Engineering

  2006 — 2010

• National University of Singapore

  Masters of Science, Chemical and Pharmaceutical Engineering

  2010 — 2011

• Carnegie Mellon University - Tepper School of Business

  Master of Business Administration (MBA), Logistics and Supply Chain Management

  2016 — 2019

Skills

• Microsoft Office
• Matlab
• Data Analysis
• Research
• Process Engineering
• Chemical Engineering
• Excel Dashboards
• Powerpoint
• Microsoft Excel
• Engineering
• Aspen Plus