Jorge H.
AI Engineer

Skills

Python

PyTorch Video

Google Scikit-learn

TensorFlow Hub

Spark

Simul

Jorge is available for hire

Hire Jorge H.

All Howdy Candidates are vetted for skills and english proficiency.

Bio

Possessing a Bachelor's and a Master's degree in Physics from a state university, this candidate demonstrates expertise in applying mathematical tools, logical reasoning, and scientific methods to practical problem-solving across various domains that utilize modeling and data analysis. The individual showcases substantial proficiency in programming as applied to fields such as Analytics, Machine Learning, and finite element simulations, as well as in control and automation systems. With robust experience in developing and implementing AI, Computer Vision, and advanced machine learning solutions, this candidate has led multidisciplinary teams and adopted MLOps practices in the sector. Furthermore, they are well-versed in documenting projects effectively and delivering impactful oral presentations in both Portuguese and English, making them particularly suited for interdisciplinary collaborations.

Technical Lead
9/1/2022 - Present

Developed and implemented AI solutions, including Computer Vision and LLM, while leading a multidisciplinary team for project execution and pre-sales initiatives, and established MLOps practices for streamlined project implementation.
Artificial Intelligence Architect
5/1/2021 - 9/1/2022

Focused on developing computer vision solutions, integrated machine learning models into production systems using RESTful APIs and worked collaboratively with a software engineering team to enhance project results.
Data Scientist
10/1/2019 - 4/1/2021

Analyzed sellout data to generate data quality KPIs and developed sales forecasting models utilizing regression techniques and time series analysis to support business decisions.
Data Scientist
7/1/2019 - 10/1/2019

Worked in business intelligence, creating predictive models to manage transportation costs and risk monitoring by processing data extracted from a local SQL server using Python libraries such as numpy, pandas, and scikit-learn.
Data Scientist
3/2/2019 - 7/2/2019

Contributed to the development of a complaint prediction model, engaging in analytics and pipeline creation while addressing a complex dataset exceeding 3 gigabytes and employing libraries like Pandas and PySpark for model building.
Graduate Student
3/2/2017 - 4/2/2019

Developed a theoretical model for generating third harmonics in microcavities, incorporating thermal effects and numerical calculations, and simulated optical modes using finite element methods to compare theoretical predictions with experimental data.