Jessica Claire
  • Montgomery Street, San Francisco, CA 94105 609 Johnson Ave., 49204, Tulsa, OK
  • Home: (555) 432-1000
  • Cell:
Seeking a Data Science/Machine Learning Position
I am looking for a full time position in the AI space, my passion is using AI powered tools and platforms to create smarter software.  
Education and Training
Bachelor of Arts: Computer Science, Expected in June 2017
University of California - San Diego, CA
GPA: 3.5​
Activities & Honors:
  • UCSD NCAA Women’s Soccer Team
  • 2-time Athletic Director Honor Roll-Gold Level
  • iLead Communication and Leadership Award
  • Machine Learning: deep learning, feature engineering, transfer learning, regression, classification, reinforcement learning
  • Languages : Python, Linux, SQL, Java, HTML, CSS
  • Frameworks/Applications: Tensorflow, BigDL, Spark, scikit-learn, Jupyter, GCP, AWS, Qubole, Anaconda, Docker, Git
Computer Vision Engineer, 11/2017 to Current
Verizon CommunicationsBridgeville, PA,
  • Building detection and classification models using Python, Tensorflow, Keras, scikit-learn to help auto-generate tags for visual assets
  • Constructing data ingestion pipeline, implementing APIs, and building model deployment framework to add deep-learning generated intelligence to our system
Deep Learning Engineer, 08/2017 to 11/2017
360PiIndianapolis, IN,
  • Using a distributed Deep Learning framework for Apache Spark, BigDL, to train an Inception V3 CNN and classify 2.4 million images for the World Bank to detect fraud amongst crowdsourced images
  • Doing feature engineering, image pre-processing, transfer learning, and fine-tuning of pre-existing ImageNet model from Caffe using inception architecture 
  • Published a customized Amazon Machine Image for deep learning in Spark to launch EC2 instances for educational purposes
  • Speaker at multiple workshops/meetups including Intel AI DevJam Night in SF (video link:
Project - Netflix Movie Recommendation System, 06/2017 to 06/2017
Syllable, ,
  • Engineered dataset for students' opinions on Netflix movies to learn a Naïve Bayes Model for classifying students to a moviegoer type
  • Used EM algorithm for binary matrix completion, then fine-tuned parameters used to recommend personalized, best unseen movies to each student 
Software Engineer, 02/2017 to 05/2017
Tijuana Red CrossCity, ,
  • Developed web-application which connects dispatchers with ambulance locations in real time, part of an end-to-end emergency dispatch system deploying in Red Cross of Tijuana, Mexico.
  • Implementing MQTT protocol, REST APIs, serializations, designing schema, improving data visualization using Python/Django and designing algorithm to route ambulances more efficiently and reduce response times.

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Resume Overview

School Attended

  • University of California

Job Titles Held:

  • Computer Vision Engineer
  • Deep Learning Engineer
  • Project - Netflix Movie Recommendation System
  • Software Engineer


  • Bachelor of Arts

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