About
I am a Generative AI Team Lead, Solution Architect, and Machine Learning Engineer with 6+ years of experience building models for natural language processing, computer vision, and tabular datasets. With a B.S. in neuroscience and an M.S. in computer science, I am especially excited about the development of neural networks and the increasing complexity of problems they can solve. Over the past several years, I have had the opportunity to work on analytics for large-scale medication adherence outreach programs, multi-task neural networks for brain microscopy image segmentation, transformer-based NLP models to detect COVID-19 outbreaks from news articles, explainable machine learning for fraud detection, and more.
Currently, I am working at Superlinear as a Generative AI Team Lead and Solution Architect.

Data Scientist & Machine Learning Engineer
Experienced in all aspects of the data science pipeline, including data exploration, feature engineering, model training, and model deployment.
- University: Georgia Tech, UMiami
- Employer: Superlinear
- Location: Brussels, Belgium
- Degree: B.S., M.S.
- Email: j.miano@outlook.com
- Languages: English, French, Spanish
Skills
Programming Languages
- Python
- SQL
- MATLAB
- Java
- C
ML & Big Data
- PyTorch
- Transformers
- Scikit-learn
- PySpark
- Dask
Visualization
- Matplotlib
- Seaborn
- Plotly
- Streamlit
- Tableau
Techniques
- Deep Learning
- Feature Engineering
- Ensemble Methods
- Unsupervised Learning
- Prompt Engineering
Data Domains
- Computer Vision
- Natural Language Processing
- Audio & Speech
- Tabular Datasets
- Time Series
DevOps & Cloud
- Docker
- Git
- Azure
- GCP
- AWS
Resume
Click here to view my resume as a PDF.
Summary
Joseph Miano
Solution Architect and Machine Learning Engineer with 6+ years of experience in natural language processing, computer vision, tabular datasets, and deep learning.
- Brussels, Belgium
- j.miano@outlook.com
Education
Master of Science in Computer Science
Aug 2020 - Dec 2021
Georgia Institute of Technology, Atlanta, GA
- Machine Learning Specialization
- Graduate Research Assistant at the Georgia Tech Research Institute
- Coursework in deep learning, computer vision, natural language processing, and machine learning theory
Bachelor of Science in Computer Science
May 2018 - May 2020
Georgia Institute of Technology, Atlanta, GA
- 2nd B.S.
- Coursework in computer science and mathematics
- Specializations in theory and artificial intelligence
Bachelor of Science in Neuroscience
Aug 2012 - May 2016
University of Miami, Coral Gables, FL
- Minors in Finance and Chemistry
- Research in cellular neuroscience
- Pre-medical track with medical shadowing experience
Internships
AI & Machine Learning Summer Associate
Jun 2021 - Aug 2021
JPMorgan Chase & Co., Remote, USA
- Developed object-oriented Python code to enable explainability and interpretability of credit risk assessment models
- Presented results and conclusions to the broader intern group and organization (20+ colleagues)
Software Engineering Summer Intern
Jun 2019 - Aug 2019
American Express, Phoenix, AZ
- Trained natural language processing machine learning models using Python to automate incident ticket routing
- Explained summer project and results to VP-level organization (40+ colleagues) during end-of-internship presentation
Work Experience
Senior Machine Learning Engineer → GenAI Lead
Mar 2023 - Present
Superlinear, Brussels, Belgium
- Lead a team of 8 GenAI-focused machine learning engineers, which includes career growth mentorship, organizational planning, and project delivery support for a project portfolio valued at €1,000,000+ in yearly revenue
- Coordinated the technical architecture, development, and productionalization of a pharmaceutical client's LLM-based applications, enabling €50,000+ of yearly cost savings via automatic translation and PII detection
- Generated €250,000+ revenue via technical architecture design, proposal crafting, and presentations to key stakeholders
- Developed convolutional autoencoders to denoise barcode images for a project with a retail partner, leading to a 15%+ lift in barcode recognition accuracy
Senior Data Scientist (AI & ML)
Feb 2022 - Mar 2023
JPMorgan Chase, New York, NY
- Engineered 100+ features for customer authentication risk assessment models, specifically to mitigate digital authentication risk
- Trained ML models to predict fraudulent customer authentication events, balancing customer service experience (false positives) with fraud risk (false negatives)
- Coordinated the explainable AI track for the inaugural 2022 JPMorgan Chase AI Summit, which brought together 10+ speakers and 100+ attendees
Graduate Research Assistant (AI & ML)
Sep 2020 - Dec 2021
Georgia Tech Research Institute, Atlanta, GA
- Implemented neural natural language processing models (RoBERTa) to automate COVID-19 outbreak detection using web-scraped news article contents
- Published a paper as first author in the Springer Lecture Notes in Artificial Intelligence as part of the 2021 Artificial Intelligence in Medicine Conference
Research Assistant (AI & ML)
Aug 2018 - Jul 2020
Neural Data Science Lab, Georgia Tech, Atlanta, GA
- Engineered a multi-task convolutional neural network for microstructure segmentation and brain area classification of mouse brain x-ray microtomography data
- Presented a joint poster at the Allen Institute BioImage Informatics 2019 Conference (funded with PURA Travel Award)
Consultant → Senior Consultant
Aug 2016 - Apr 2018
CVS Health, Woonsocket, RI
- Developed predictive models to identify patients at risk of non-adherence, enabling targeted outreach programs across 5,000+ CVS stores nationwide, improving medication adherence rates in outcomes-based contracts
- Quality-tested 50+ features for an enterprise-level predictive modeling project in collaboration with stakeholders from several departments
Projects
Hover or click on the images below to get a summary and link for each project.




Papers
While studying at the Georgia Institute of Technology, I had the opportunity to contribute to 4 published papers and complete a thesis.
Using Event-Based Web-Scraping Methods and Bidirectional Transformers to Characterize COVID-19 Outbreaks in Food Production and Retail Settings
1st Author | 2021
A three-dimensional thalamocortical dataset for characterizing brain heterogeneity
4th Author | 2020
Multi-task learning for neural image classification and segmentation using a 3D/2D contextual U-Net model
Thesis | 1st Author | 2020