Abraham Escalante
Senior Machine Learning Engineer at Centre Lane Trading
Old Toronto, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolAbraham Escalante is a Senior Machine Learning Engineer with 11 years of experience building production-grade ML systems and deploying models at edge and cloud scale. He has led end-to-end MLOps and deep learning efforts across finance, security, and edge-computer-vision domains—shipping sports-betting frameworks, fraud-detection prototypes, and dozens of deployed detection models from AWS SageMaker to embedded kiosks. Skilled in PyTorch, TensorFlow, Python, OpenCV and Azure/AWS tooling, he routinely turns research prototypes into resilient APIs and CI/CD pipelines that serve high-throughput real-world traffic. He also contributes to core scientific Python via SciPy, improving statistical robustness (e.g., edge-case and NaN handling in scipy.stats), reflecting a focus on correctness as well as performance. Based in Toronto, he blends hands-on model engineering with pragmatic product judgment, repeatedly converting stakeholder experiments into production features. An intriguing thread through his work is automating creative pipelines—from 3D model generation for AR to rapid fever-detection kiosks—demonstrating an appetite for applied, cross-disciplinary solutions.
11 years of coding experience
10 years of employment as a software developer
Bachelor of Science (BS), Computer Science, Bachelor of Science (BS), Computer Science at Tecnologico de Monterrey, Campus GuadalajaraMaster’s Degree, Computer Science, Master’s Degree, Computer Science at University of Toronto
Spanish, English
Stackoverflow
45reputation
3kreached
1answer
2questions
Github Skills (14)
statistics10
algorithms10
scipy10
python10
numpy10
testing9
data-structures8
data-structure8
h2o6
slug6
cross-validation6
r6
django6
django-templates6
Programming languages (1)
Github contributions (5)
scipy/scipy
Mar 2015 - Aug 2015
SciPy library main repository
Role in this project:
Back-end Developer
Back-end DeveloperContributions:94 commits, 31 PRs, 196 comments in 5 months
Contributions summary:Abraham made several contributions related to the `scipy/scipy` library's statistical functions. They enhanced the `stats.mode` function to handle empty arrays and added scalar tests, demonstrating an understanding of edge cases. The user also deprecated and removed several functions (`signaltonoise`, `histogram2`, `ss`, and `square_of_sums`), suggesting a role in maintaining code quality and removing outdated functionalities. Additionally, they contributed code to handle nan inputs in statistical functions, improving robustness.
scipypythonscientific-computing
aeklant/.vimrc
Feb 2015 - Mar 2020
Contributions:5 pushes in 5 years 2 months
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