About Me

Machine Learning Engineer | Computer Vision Scientist

I am an inquisitive and energetic team leader that enjoys deep dives into data and real-world problems with experience leading projects from inception to commercial deployment. Coming from a startup background, I have a versatile set of skills, where I can come in develop on Android, all the while building the machine learning models that power the app. At that core I am an applied engineer that loves to build and tinker.

Portfolio

My Work
CLIP Exercise Recognition

CLIP Exercise Recognition

Side Project
DAGER: Deep Age, Gender and Emotion Recognition

DAGER: Deep Age, Gender and Emotion Recognition

Product
Driver Awareness

Driver Awareness

Product
Car Make/Model/Color Recognition

Car Make/Model/Color Recognition

Product
License Plate Recognition

License Plate Recognition

Product
Parent-Offspring Resemblance

Parent-Offspring Resemblance

Research
Video Face Recognition

Video Face Recognition

Research
Face Recognition for Web-Scale Datasets

Face Recognition for Web-Scale Datasets

Research

Resume

9 Years of Experience

Experience

2021-2022
Peloton Interactive

Staff Machine Learning Engineer

  • Prototyped multi-signal exercise repetition counting with an off-by-zero error of > 95%.
  • Supported failure and metric tracking for releases of exercise recognition and repetition counting.
  • Headed ML prototyping on multi-disciplinary team for unreleased product, see patent below.
  • Led best practices initiative for small, agile computer vision team.
2020-2021
Samsung Next

Senior Staff Machine Learning Engineer

  • Developed physical exercise recognizer and repetition counter including data collection, neural network development, model training, and real-time iOS implementation with off by 1 error of 1%.

  • Led and implemented tech transfer with external vendor for 2 month timeline on custom Samsung hardware running Android for exercise recognition.

  • Collaborated with Samsung AI Centers to productionize their R&D technologies for facial analysis.

  • Built reproducible ML workflow including versioning data, training runs, results, and models.

2014-2020
Sighthound, Inc.

Computer Vision Scientist

2007-2014
UCF Center for Research in Computer Vision

Graduate Research Assistant

Education

2007-2014
University of Central Florida

Ph.D. and M.Sc. (Software Engineering Track) in Computer Engineering

Dissertation: Taming Wild Faces: Large-Scale, Real-World Face Recognition in Still and Video Imagery
Advisor: Professor Mubarak Shah, Director of Center for Research in Computer Vision
2003-2007
University of Central Florida

B.Sc. in Computer Engineering, Magna Cum Laude

Thesis: A Scalable and Efficient Outlier Detection Strategy for Categorical Data
Advisor: Professor Michael Georgiopoulos, Dean and Director of Machine Learning Lab at UCF

Skills

Python

OpenCV

Caffe

PyTorch

C++

Tensorflow

Android

iOS

Expertise

Computer Vision

Face Recognition

Action Recognition

Object Detection

Machine Learning

Deep Learning

Contact

Get in Touch

New York City

ortizeg@gmail.com