Freddy Dick Salazar Valverde

• Prototyped LLM models using Langchain with data pipelines utilizing Lang Chain, OpenAI and transformers to document analysis, chatbots, abstract and classify.
• Prototyped novel AI architectures utilizing deep learning frameworks like Keras, Tensorflow or Pytorch to video analytics.
• Developed and implemented machine learning algorithms to classify, detect, segment, pose estimation to industrial applications.
• Followed industry innovations and emerging trends through scientific articles, conference papers or self-directed research to prototype and implement in real world.
• Identified potential problems with existing ML, DL and AI systems and proposed solutions for improvement.
• Integrated pre-trained ML and AI models into web applications using frameworks such as TensorFlow or PyTorch.
• Developed custom APIs for deploying trained models onto cloud services such as AWS, Azure or on premise devices like a GPU server or embedded devices like NVIDIA Jetson, etc.
• Technical lead of some projects of different industrial projects.
• Industry 4.0 Team developing projects related to OCR, video analytics in real time using Jetson Embedded devices applied to industrial security or solutions to improve production and KPI's, implement computer vision models, classification, object detection, segmentation, pose estimation and streaming.

• Research, development and experimentation in a Natural Language Processing and CSIRT information security project.
• Prototyped ciber security application using LLM - ChatGPT, Transformers, AWS, Amazon Sagemaker with Python.
• Collaborated with team of another countries to develop effective solutions related to cibersecurity.
• Tested AI pipeline in applications prior to release and identified issues requiring resolution.

• Developed and implemented software solutions to improve the efficiency of existing systems.
• Detected and resolved data quality issues and discrepancies for integrity and quality control.
• Created complex SQL queries for reporting purposes.
• Modified existing software systems to enhance performance and add new features.
• Participated in code reviews and provided feedback on best practices for database development.
• Designed databases using ER diagrams to reflect entity relationships between different objects within a system.

• Created status reports on operational activities.
• Reviewed project specifications, identifying and remedying potential issues that could result in development delays.
• Participated in code reviews conducted by senior developers or architects.
• Documented program development and subsequent revisions with comments for easy comprehension.
• Designed, developed and implemented backend software to support system product concepts.

Freelancer

Big Bang Group - Current

• Development of a MVP to extract important KPI from public information about Stock Exchange using transfer learning with pre-trained LLM models.

Researcher

Artificial Intelligence and Robotics Laboratory FIIS UNI 2023

• Research in brain tumor classification and segmentation of magnetic resonance imaging using Deep Learning algorithms.
• Transfer learning of segmentations algorithms like U-Net and others modifications described in papers, optimizing parameters and hyper-parameters to improve results.

Freelancer

Proetica Org. 2023

• Development and deployment of a predictive machine learning model to predict if a Forest Management Plan is legal or illegal.
• Implementation of API in AWS architecture using RDS, EC2, S3.
• Develop simple web page with Streamlit to predict new results.

Freelancer

Artificial Intelligence and Robotics Laboratory FIIS UNI 2021-2022

• Support to implement AI Server in laboratory.
• Identified needs of future researchers promptly and efficiently.

Volunteering

Equilibrio NGO 2021

• Development and deployment of first web landing page of NGO.
• Implementation frontend and backend in AWS architecture.
• Leading young team of different universities.

Freelancer

Feedback Project 2020 - 2021

• Development of Feedback survey application with facial emotion recognition using Deep Learning and Tensorflow.
• Deployment of survey AI in phone application to use in real time survey.