Where I've worked.
My objective with the University of Waterloo's co-op program was to diversify my work placements and see where in tech my interests lie.
With the projects and co-ops that I have done I am quite confident now that I want to work as a Machine Learning Engineer or Researcher and preferably with products dedicated towards knowledge management and tools for thought.
Machine Learning Developer
MARVL
- Fine-tuned Mistral for sequence classification tasks achieving a 98% accuracy.
- Built a conversational-RAG model with 'infinite' memory with < 10s latency
- Developed speech-to-text pipeline for sales agents to automate CRM tasks.
Langchain
FastAPI
AWS EC2
AWS Lambda
HuggingFace
Backend Developer
Martinrea
- Built a compiler for conversion from a custom language for server abstraction to a dockerized Django application that saves 5 hours weekly on development time.
- Co-engineered FactoryEngine - a platform for handling all data within a factory—users, inventories, devices, streams.
Django
React
Docker
Postgres
Redis
Security Developer
Huawei
- Delivered Huawei's LWC project for IoT-based cryptographic operations.
- Designed and implemented Huawei's Trusted Data Exchange platform in Golang.
C
C++
Golang
Testify
mbedTLS
Google Test
Post-Quantum Cryptography Software Developer
University of Waterloo
- Engineered the architecture for the post-quantum signature schemes of the liboqs library used by Microsoft and Cisco
- Increased XMSS signing speed by 40% by using pthreads to parallelize public-key generation.
C
C++
OpenSSL
What I've worked with
Languages
- Rust
- Python
- Golang
- Typescript
- C/C++
- Java
Frameworks / Libraries
- Pytorch
- Scikit-learn
- Transformers
- Django / FastAPI
- Numpy
- Streamlit
- nltk / spacy
- React
- Next.js
Tools
- Docker
- Nginx
- Kubernetes
- Postgres
- Redis
- MongoDB
- Jupyter Notebooks
Infrastructure
- AWS
- Brev.dev
- Vercel
- BentoML
- Railway