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