Erick Gonzalez

Experience

• 

  Giga Computers

  Jan 2020 - Mar 2020

  Software Developer

  Competence in Creation and Design in Ionic Framework: Capable in creating and designing applications using the Ionic Framework, with a solid understanding of developing cross-platform mobile apps with HTML, CSS, and JavaScript.Proficiency in MySQL Database Management: Skilled in managing MySQL databases, including data modeling, querying, optimization, and ensuring data integrity.Familiarity with Creation and Design of Java Systems: Familiar with developing Java systems, utilizing object-oriented principles and design patterns to create functional solutions.Problem Analysis and Resolution: Able to analyze problems, identify root causes, and work towards effective solutions with some level of autonomy.Experience in Creation and Consumption of Services: Experienced in creating and consuming services, working with RESTful APIs, and integrating external APIs to enhance application functionality.Bug Fixing: Competent in identifying and resolving software bugs through debugging techniques, testing, and collaborating with team members.Understanding of Efficiency Measurement: Familiar with measuring and optimizing application efficiency through profiling and basic code refactoring practices.Meeting Daily and Weekly Goals: Demonstrated ability to set and meet daily and weekly goals, ensuring timely completion of tasks and contributing to project progress. Show less

• 

  Jalasoft

  Sept 2021 - now

  • JCE Software Engineer

    Jan 2023 - now

  • Software Engineer

    Sept 2021 - now
• 

  Anyone AI

  Jan 2023 - now

  Machine Learning Engineer

  Worked with industry experts developing high-quality data science and machine learning projects for the industry:● Developed a sentiment analysis model for movie reviews by manipulating non-traditional data, performing preprocessing, normalization, and TF-IDF vectorization.Tokenized the reviews and trained a custom word embedding using Word2Vec.Achieved an 81% accuracy and an 89% ROC curve in detecting positive and negative opinions.● Developed a Machine Learning model for vehicle classification by training and evaluating different models, including Multi-layer Perceptron, LeNet, and ResNet50, on a pre-built dataset of 196 classes. Achieved an 83% accuracy in predicting the type of car in images, with ResNet50 performing the best.● Developed a Machine Learning API system that receives images, predicts their content using the ResNet50 convolutional neural network model, and achieves a 93% prediction score. Implemented API endpoints, utilized a Redis database, and built the system with Docker and Docker Compose. Conducted stress tests with Locust to assess API capabilities and limits● Developed a credit risk scoring model by obtaining and analyzing data using specialized libraries (Matplotlib/Seaborn). Preprocessed the data through feature selection, outlier detection/handling, feature imputation/normalization/standardization, and categorical feature encoding. Created a baseline model using randomized search and cross-validation techniques with Scikit-learn in Python, achieving a training ROC AUC score of 74% and a validation score of 70%● Product detection for in-store inventory management with YoloV5: Applied computer vision techniqueto detect products in images of supermarket shelves. Built an API service, backed by a machinelearning model for object detection (YoloV5) that returned the bounding boxes with the location ofexistent and missing products, the results achieved were highly precise, demonstrating a remarkable level of accuracy and effectiveness. Show less