Jessica Claire
  • Montgomery Street, San Francisco, CA 94105 609 Johnson Ave., 49204, Tulsa, OK
  • Home: (555) 432-1000
  • Cell:
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Professional Summary

Innovative Artificial Intelligence / Computer Vision / Machine Learning Engineer possessing strong mathematical skills and detailed knowledge of machine learning evaluation metrics and best practices. Offering almost four years of experience creating programs and algorithms to enable machines to take actions without being directed. Expertise in predictive analysis, data mining, and computational statistics. Logical and detailed professional with exceptional Python coding and typed language skills such as C++.

  • Programming Languages: Python, C++, C.
  • Deep Learning Frameworks: PyTorch, Tensorflow, Keras.
  • Programming Libraries: OpenCV, CUDA, numpy, pandas, scikit-learn
  • Configuration Management: Git
  • Web Frameworks and Database: Flask, S3
  • Platforms: Amazon Web Services (AWS), Docker
  • Data Visualization tools: Matplotlib, Seaborn
Work History
Computer Vision/Artificial Intelligence Engineer, 08/2021 to 11/2021
AppenSeattle, WA,
  • Collaborated with multi-disciplinary product development teams to identify performance improvement opportunities and integrate trained models.
  • Expertise in training and deploying CNN, LSTM, and other Sequence models on AWS using PyTorch, Tensorflow.
  • Collected, annotated, and classified data for developing action recognition ML models.
  • Turned unstructured data into useful information by auto-tagging images.
  • Developed ML algorithms to analyze huge volumes of historical data to make predictions.
  • Designed machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.
  • Researched and implemented best practices to improve existing machine learning infrastructure.
Computer Vision Intern, 05/2021 to 08/2021
AppenDallas, TX,
  • Used: Python, Pytorch, Tensorflow
  • Architected and built an exceptional heuristic model designed for human pose estimation
  • Orchestrated the process of obtaining, processing, and labeling data.
  • Pioneered initiatives focused on implementing problem-solving strategies for ML models.
  • Produced high-quality documents, spreadsheets, and presentations for internal and customer-facing needs.
  • Sorted and organized files, spreadsheets, and reports.
  • Saved $25,000 by implementing cost-saving initiatives that addressed long-standing problems.
Computer Vision Intern, 01/2021 to 05/2021
Instra.AICity, STATE,
  • Python, Tensorflow, AWS
  • Worked on models like YOLOv5, MIR model, continuous learning, data augmentation models.
  • Researched, developed, and evaluated SOTA Deep Learning models for classification, object detection, and Semantic Segmentation. Data analysis and Data Preparation pipeline development.
  • Developed text recognition models using Amazon Text Recognition and Amazon Textract. Used S3 bucket, IAM role, EC2 instance, Amazon Sagemaker.
  • Designated to engage in projects that involved managing and streamlining backend development processes.
  • Aligned the organization for growth through training and testing models as well as obtained data from multiple sources.
  • Propelled innovation in working with AWS Lambda and established annotation files for the data.
  • Enhanced quality outcomes in driving ML model development efforts by writing python scripts for multiple projects.
  • Managed team of 50 employees, overseeing hiring, training, and professional growth of employees.
Master of Science: Electrical Engineering, Expected in 12/2021
Illinois Institute of Technology - Chicago, IL,

GPA: 3.57

  • Awarded First Place for best Master's Thesis Research in ECE Day Research Competition within ECE Department.
  • Teacher Assistant (TA): ECE 308. Signals and Systems
Bachelor of Technology: Electrical Engineering, Expected in 07/2019
Techno InterNational NewTown - India,

GPA: 7.8/10



  • Python, Tensorflow, MATLAB
  • Implementation of the key-point based video object detection model, CenterNet and added a convLSTM/RNNmodel to enhance detection performances for videos


  • C++, Labview
  • A dynamic model of the exoskeleton, thumb (4DOF) and index finger (3DOF) has been developed based on fourbar mechanism in view of grabbing all possible things indistinctively.
  • Non linear rehabilitation practises have been carried out by adopting force control by means of force sensors.


  • C, MATLAB, Convolutional Neural Networks
  • Robust dataset of different images of car plate numbers were gathered.
  • The algorithm was such that it would recognize the state from the car plate number.
  • The model was based on convolutional neural networks.
  • We used MATLAB R2017a.
  • Jessica Claire, P Claire, N Saha, P Chattopadhyay, ”Automatic number plate recognition using CNN based selfsynthesized feature learning,” 2017 IEEE Calcutta Conference (CALCON), 378-381
  • PClaire, Jessica Claire, SGhosh, MFOrlando,”Force control of an index finger exoskeleton for rehabilitation purpose,” 2018 IEEE Applied Signal Processing Conference (ASPCON), 183-187.

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Resume Overview

School Attended

  • Illinois Institute of Technology
  • Techno InterNational NewTown

Job Titles Held:

  • Computer Vision/Artificial Intelligence Engineer
  • Computer Vision Intern
  • Computer Vision Intern


  • Master of Science
  • Bachelor of Technology

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