Eliano Anile
Software Engineer II at Stripe
Toronto, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolEliano Anile is a Software Engineer II based in Toronto with eight years of experience building performant systems at scale across Stripe, AWS, Intel, and Google. A University of Toronto Computer Engineering graduate with an AI minor and high honors, he blends systems-level thinking with practical ML-oriented tooling. At AWS he progressed from SDE I to II, and his work spans telemetry, FPGA power analysis, and production services, demonstrating comfort across hardware-adjacent and cloud-native stacks. He contributes to notable open-source projects like Rasa—improving NLU model visualization—showing a knack for making complex model diagnostics more interpretable. Known for iterating release processes and improving developer-facing tooling, he brings a mix of measured rigor and product-minded curiosity. Outside core engineering, his tutoring background hints at strong communication and mentorship skills that help bridge technical complexity for teammates.
8 years of coding experience
5 years of employment as a software developer
Bachelor of Engineering - BE, Computer Engineering, AI Minor, 3.93, High Honors, Bachelor of Engineering - BE, Computer Engineering, AI Minor, 3.93, High Honors at University of Toronto
Stackoverflow
1reputation
0reached
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Github Skills (12)
nlu10
machine-learning10
nlp10
rasa10
python10
plot10
natural-language-processing10
matplotlib10
chatbot9
googlebot9
bots9
conversation8
Programming languages (2)
Github contributions (5)
RasaHQ/rasa
Nov 2020 - Dec 2020
💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
Role in this project:
ML Engineer
ML EngineerContributions:7 reviews, 10 commits, 10 comments in 8 days
Contributions summary:Eliano primarily contributed to the improvement and modification of plotting functionalities within the Rasa NLU framework. They refactored and renamed plotting functions, enhancing the visualization of model performance, specifically confidence distributions. Their contributions involved changes to the comparative histogram plots and example usage, demonstrating a focus on data visualization and model evaluation within the context of conversational AI. The user also integrated changes from the master branch and performed code formatting.
nlupythonbotspeech-recognitionbotkit
ChrisDryden/ECE496
Nov 2020 - Mar 2021
Capstone project in detecting artifacts in EEG's for predicting seizures in infants in supervision of Prof. Bardakjian
Contributions:11 reviews, 9 PRs, 39 pushes in 4 months
capstonedeep-learningmachine-learningsupervisionartifacts
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