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| # Jeremy Pinto | |
| header: | |
| title: Senior Applied Research Scientist | |
| location: Montreal, Canada | |
| email: jerpint [at] gmail [dot] com | |
| phone: phone number upon request | |
| social: | |
| blog: | |
| text: "Blog • www.jerpint.io" | |
| url: https://www.jerpint.io/ | |
| icon: 📝 | |
| github: | |
| text: github.com/jerpint | |
| url: https://github.com/jerpint | |
| icon: fab fa-github | |
| linkedin: | |
| text: linkedin.com/in/jeremy-pinto | |
| url: https://linkedin.com/in/jeremy-pinto | |
| icon: fab fa-linkedin-in | |
| hackernews: | |
| text: HN/jerpint | |
| url: https://news.ycombinator.com/user?id=jerpint | |
| icon: fab fa-hacker-news | |
| huggingface: | |
| text: HF/jerpint | |
| url: https://huggingface.co/jerpint | |
| icon: 🤗 | |
| youtube: | |
| text: YT/jerpint | |
| url: https://youtube.com/@jerpint | |
| icon: fab fa-youtube | |
| Chat with my resume 👉 [jerpint.io/resume](https://www.jerpint.io/resume) | |
| ## Summary | |
| Senior applied research scientist with 7+ years of experience modeling, training and deploying production-ready deep learning pipelines. | |
| Led the development of award-winning LLM prompt-hacking research (EMNLP 2023 Best Theme Paper) and contributed to a successful MOOC reaching 8000+ participants. | |
| Specialized in: | |
| - Developing production-ready computer vision and NLP solutions | |
| - Bridging state-of-the-art research with practical business applications | |
| - Implementing and securing large language model workflows | |
| - Leading technical workshops and mentoring ML practitioners | |
| Stuff I build for fun: | |
| - I maintain an ML-focused blog where I post things like [using ControlNet to animate the Game Of Life](https://www.jerpint.io/blog/diffusion-gol/") | |
| - I post tutorials on YouTube like [how to summarize YouTube videos using GenAI](https://www.youtube.com/watch?v=WtMrp2hp94E) | |
| ## Key Achievements | |
| - Led HackAPrompt competition with 2800+ participants from 50+ countries, resulting in EMNLP 2023 Best Theme Paper | |
| - Core contributor of Buster, an open-source RAG tool, with 200+ github stars | |
| - Co-authored deep learning course content reaching 8000+ global participants | |
| - Published gender identification algorithm for medical voice analysis, currently integrated in iOS app | |
| ## Work Experience | |
| ### Senior Applied Research Scientist | |
| #### Mila - Quebec Artificial Intelligence Institute | Sept 2018 - Present | |
| **Key Responsibilities & Achievements:** | |
| - Architected and implemented production-ready deep learning solutions for organizations | |
| - Mentored SMEs through AI adoption programs, resulting in successful implementation of ML solutions in the Canadian AI ecosystem | |
| - Created and delivered hands-on computer vision workshops for 200+ participants | |
| - Supervised MSc. students during their internship | |
| - Co-instructor for ["Deep Learning Essentials"](https://www.edx.org/learn/deep-learning/universite-de-montreal-deep-learning-essentials) MOOC on EdX (8000+ participants), developed and delivered content on Convolutional Neural Networks and ML tools | |
| ### Lead Data Scientist | |
| #### Focus21 | May 2017 - June 2018 | |
| **Key Achievements:** | |
| - Developed proof-of-concept medical imaging systems for x-ray diagnostics using Mask R-CNN | |
| - Implemented reinforcement learning algorithms for industrial robotics in simulated environments | |
| - Implemented algorithmic trading strategies and analysis tools | |
| ## Skills | |
| **AI/ML Technologies:** | |
| - Generative AI: ChatGPT, Claude, LLaMa, cursor/copilot, Hugging Face {transformers, diffusers} | |
| - Deep Learning: PyTorch, Lightning, TensorFlow, Keras, Jax | |
| - ML Tools: Scikit-Learn, pandas, numpy, scipy, WandB, CometML, tensorboard | |
| **Software Development:** | |
| - Languages: Python, Bash, Javascript, Matlab, LaTeX, Markdown | |
| - API & Web: FastAPI, Gradio, Hugging Face | |
| - Data Processing: pandas, NumPy, hf-datasets | |
| **Cloud & Infrastructure:** | |
| - DevOps: Git, CI/CD, Docker, SLURM | |
| - Cloud Platforms: AWS, Azure, Heroku | |
| - Databases: MongoDB, SQLite | |
| - Editors: VSCode, (neo)vim | |
| **MLOps:** | |
| - Experiment Tracking: WandB, CometML, TensorBoard | |
| - Data Version Control: Hugging Face datasets, deeplake, dvc | |
| - Model Serving: TorchServe, ONNX, BentoML, Docker | |
| **Languages:** | |
| - English (Native), French (Native) | |
| - Hebrew (Limited Working), Spanish (Basic) | |
| ## Education | |
| ### Systems Design Engineering - Vision and Image Processing (VIP) Lab | |
| #### University of Waterloo, MASc. | 2015-2017 | |
| - Thesis: "Cancer Classification in Human Brain & Prostate Using Raman Spectroscopy & Machine Learning" | |
| - Led research resulting in 2 peer-reviewed publications | |
| - Trained and deployed urban sound classification models within iOS apps | |
| ### Engineering Physics | |
| #### Polytechnique Montréal, B. Eng. | 2010-2014 | |
| - Graduated with Distinction | |
| - Awarded DeVinci Profile and International Profile | |
| - Developed novel acoustic camera system for holography validation | |
| ## Projects | |
| ### HackAPrompt (2023) | [https://paper.hackaprompt.com/]() | |
| - Led development and implementation of global prompt-hacking competition | |
| - Tech Stack: Python, HuggingFace Transformers, PyTorch, FastAPI | |
| - Impact: 2800+ participants, 50+ countries, EMNLP2023 Best Theme Paper | |
| - Surveyed novel methodologies for testing LLM security | |
| ### Buster (2022-2024) | [https://github.com/jerpint/buster]() | |
| - Core contributor of open-source RAG tool with citation capabilities and response-monitoring | |
| - Tech Stack: Python, OpenAI, Gradio, Pinecone, MongoDB, Deeplake | |
| - Adopted in research projects at [Mila](https://huggingface.co/spaces/mila-ai4h/AIR) and the [OECD](https://oecd.ai/en/air/) | |
| - 200+ GitHub stars | |
| ### VoiceCollab (2021-Present) | [www.voicecollab.us]() | |
| - Lead ML developer for gender-affirming voice care deep-learning models | |
| - Implemented production-grade audio processing pipeline | |
| - Tech Stack: PyTorch, ONNX, Swift, Docker, MongoDB, Firebase | |
| - Peer-reviewed publications | |
| ## Selected Publications | |
| - Schulhoff, S, J. Pinto et al. (2023). "Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs through a Global Scale Prompt Hacking Competition" | |
| EMNLP2023 Best Theme Paper Award | |
| - Bensoussan Y, Pinto J, et al. (2021). "Deep Learning for Voice Gender Identification: Proof-of-concept for Gender-Affirming Voice Care." Laryngoscope | |
| - J. Pinto (2017), "Cancer Classification in Human Brain and Prostate Using Raman Spectroscopy and Machine Learning." MASc. Thesis, UWSpace. | |
| Full publication list: [Google Scholar](https://scholar.google.com/citations?user=e-N_8owAAAAJ) | |
| ## Professional Interests & Activities | |
| - Technical Writing: Maintain ML-focused blog at [www.jerpint.io]() | |
| - Public Speaking: Regular invited speaker at AI conferences and workshops | |
| - Hobbies: Rock climbing, hockey, guitar, drums, travel | |