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Research Engineering Leader, Object Indexing @ Reality Labs (Meta)
Do you want to help bring science fiction into reality? Augmented Reality will help transform society through bringing people closer and providing us all with superhuman powers: Imagine going on a vacation and your glasses telling you where all the utensils and plates are in a place you've never visited before. Imagine going to a museum the next day, having your friend walk along beside you, even though they might be thousands of miles away. Imagine being able to look at any painting and instantly know who painted it, and recall previous work you've seen from that artist before. The opportunities are limitless. While we are already able to project digitally into the real world, a whole wave of experiences require us to understand the real world so we can be interact with it in AR. My research team is focused on advancing state of the art Computer Vision and deep learning algorithms in order to understand the world around us - updating this understanding as the world evolves, in real time. If you are passionate about computer vision, deep learning, and bringing about the future, then this is the team for you! Feel free to reach out to me to learn more!
Victoria University of Wellington
BSc, Computer Science
January 1, 1997 – January 1, 2000
Victoria University of Wellington
BCA, Information Systems
January 1, 1997 – January 1, 2000
Meta
Research Engineering Manager
December 1, 2021 – Present
Seattle, Washington, United States
Amazon
Senior Manager, Machine Learning (Applied Science)
July 1, 2015 – February 1, 2022
Amazon
Software Development Manager
May 1, 2014 – June 1, 2015
Dealflow.com
Advisory Board Member
February 1, 2014 – February 1, 2017
New York City Metropolitan Area
CreditSights
CTO
October 1, 2004 – April 1, 2014
New York City Metropolitan Area
BearingPoint
Consultant
January 1, 2001 – October 1, 2004
Worldwide
The Web Ltd
Web Developer
December 1, 1999 – January 1, 2001
Wellington, Wellington, New Zealand
Helios
Developer
September 1, 1998 – November 1, 1999
Wellington, Wellington, New Zealand
Shell Oil Company
Intranet Developer
October 1, 1997 – March 1, 1998
Wellington, Wellington, New Zealand
CreditSights Mobile (beta)
October 1, 2012 – Present
CreditSights customers wanted a way to read our research in areas with no connectivity (e.g. the subway or on an airplane). Whenever they connect with this application, it downloads the latest research relevant for them for their perusal offline. Rather than develop native applications for different devices, we decided to create an HTML5 web application that could be run on a variety of phones and tablets (concentrating primarily on the iPhone and iPad). Technologies Used: * Front End: JavaScript (jQuery, jQuery Mobile, JSON), HTML5 (local storage) / CSS (media queries) * Back End: C#, MVC3, WebAPI 2, SQL Server 2008, C#, Topic Maps
CreditSights Ratings
January 1, 2012 – Present
CreditSights Ratings is a quantitative finance model that provides medium term credit ratings for over 3,100 companies in North America and Europe. The website allows users to drill down to individual companies to see the history of the ratings and the impact of the various inputs in the model. They are also able to create portfolios of the companies they are interested in and experiment to see the impact of different GDP scenarios. The model is based on linear & logistical regression of variables hand-picked by the CreditSights fundamental research team. Technologies Used * Front End: C#, MVC3, JavaScript (jQuery, jQuery UI, JSON & DataTables), HTML5 / CSS * Back End: SQL Server 2012 & SSIS, C#, Stata, Logistical Regression Models
Data Warehouse & Business Intelligence
January 1, 2005 – Present
I applied my experience from working with the Verizon billing system when architecting and leading the development of the CreditSights data warehouse. The initial incarnation combined data from various sources (website usage, article metadata, accounting &CRM data), and surfaced it to the sales team, enabling them to more effectively convert prospects and retain existing customers. We then incorporated over 20 years’ financial information on more than 10,000 companies from multiple providers, which enabled the development of our CS Ratings models (logistical regression). We recently incorporated our systems monitoring information, and are looking into ways to use alternative machine learning models to improve systems reliability. Technologies Used * SQL Server, SSIS / ETL, QlikView, Hostmon, logistical regression; data from Bloomberg, FactSet, S&P
Cultural Fit Analysis
The candidate has a diverse background spanning large corporations (Meta, Amazon, BearingPoint), a financial tech company (CreditSights), and early web development roles. Their experience in leading innovation, driving significant improvements in recommendation systems, and establishing data warehouses aligns with a culture of continuous improvement and data-driven decision-making. However, the target role is 'OpenStack Engineering Manager', and there is no explicit mention of OpenStack, cloud infrastructure, or related technologies in their resume or projects. This represents a significant gap in direct cultural and technical alignment for the specific target role, despite strong general engineering management skills.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership, strategic thinking, and problem-solving skills through their management roles and project descriptions. Their experience in leading international teams, managing multiple work streams, and guiding businesses through disasters indicates high operational resilience and team management capabilities. The focus on improving developer productivity and customer satisfaction through Agile processes highlights a strong fit for collaborative and results-oriented environments.