Austin, Texas, United States
Product-focused AI /ML/ Data Science engineering lead working at the intersection of machine learning, robotics, and large-scale autonomous systems. I’ve spent the last several years building products and leading teams working on autonomy evaluation, simulation, and real-world performance measurement for self-driving systems at scale. My focus is on turning complex real-world behavior into measurable systems: - Building large-scale evaluation frameworks for autonomy safety, reliability, and operational performance, translating real-world fleet behavior into deployment and launch-readiness signals - Developing state-of-the-art simulation and scenario mining systems for long-tail and safety-critical edge cases using CLIP-based models, vision-language models (VLMs), and multimodal foundation models for scenario discovery and test generation - Designing decision-grade metrics that connect model behavior, perception outputs, and system-level performance to real-world autonomy outcomes - Working across engineering, product, and operations to define launch readiness criteria, guide autonomy expansion decisions, and translate evaluation signals into deployment actions Previously focused on commercial marketplace optimization, routing/dispatch, pricing and predictive modeling. More recently, my work has shifted heavily into autonomy evaluation and physical AI systems—bridging ML, robotics, and real-world deployment decisions. Expertise in: Machine Learning, Robotics systems at scale, Autonomy Evaluation, Simulation, Routing/Dispatch, Optimization, Safety & Reliability Metrics, Statistical Inference, Insight Analytics, Executive-level communication I enjoy working on hard systems problems where decisions have real-world impact and where measurement, not just modeling, drives outcomes.
I design and build autonomy evaluation and simulation systems used to assess safety, reliability, and operational performance of large-scale autonomous vehicle systems. In parallel, I provide technical leadership to a data science team working on evaluation frameworks, scenario mining, and predictive modeling for autonomy systems. Key areas of Work: - Designing predictive evaluation frameworks for autonomy and marketplace KPIs across operating domains - Building large-scale scenario mining systems (including CLIP-based and multimodal approaches) to surface rare and safety-critical driving situations and build accurate and wide-spanning tests. - Defining safety and performance metrics used in launch readiness and expansion decisions - Partnering with engineering and product teams to translate autonomy behavior into decision-grade signals - Building system to enable scalable human-in-the-loop labeling, precision/recall benchmarking, golden dataset generation, and evaluate metric drift of key data miners. This role sits at the intersection of ML systems, robotics evaluation, and real-world deployment decisions.
As a Tech Lead in Data Science at Cruise, I served as a Subject Matter Expert for our safety methodology and our our dynamic selection of operating zone optimization to support the expansion of our driverless operating domain.
Architecting analytics and metrics tracking to define strategy for the Technical Product Management organization and modeling of safety and reliability metrics.
Spearheaded data science projects that improve the customer experience of Oracle Financials Cloud products. Lead New Products team in Oracle Fusion Financials. The team comprised of data scientists, software engineers, and a product manager.
Built a high-speed desktop trading application using React, Node.js, socket.io, and d3.js. Built the tool to manipulate, filter and visualize real-time stock ticker data for traders so that traders could have full control to customize the data they're interested in analyzing.
Redesigned the Dragon Spacecraft Production floor by developing a Python algorithm that minimized worker inefficiencies, unnecessary movements, and handled scheduling for prioritized tools. The goal was to provide SpaceX with the to manufacture six Dragons in one year.