AI/ML Engineer
B.S. Computer Science (AI/ML), Minor in Business
Incoming @ Shopify | Ex-Microsoft
👋🏾 Hi! I’m Tawana, a Computer Science student at Carleton University specializing in AI/ML with a minor in Business (GPA 3.95/4.0). I’m passionate about building intelligent, scalable systems through experiences in cloud engineering, distributed diagnostics, and machine learning.
💻 I’ve interned at Microsoft and Raven Connected, where I architected distributed diagnostic engines, computer vision pipelines, and multi-task learning systems. This summer, I’ll be joining Shopify as an Applied ML Engineer Intern on the Unified Recommender team. I enjoy working at the intersection of machine learning, systems design, and cloud platforms to create tools that make a real-world impact.
- Unified Recommender team.
Duration: May 2026 - August 2026
- Engineered a Counterfactual Data Augmentation pipeline using vLLMs to perform latent-space interventions, generating paired samples that decouple class labels from environmental noise to eliminate spurious correlations.
- Architected an automated end-to-end labelling pipeline using Depth Anything V3 and SAM 3 to generate semantic Bird's-Eye-View (BEV) occupancy grids, mapping in-cabin spatial relationships and Human-Object Interactions (HOI).
- Developed a Unified Multi-Task Learning (MTL) architecture leveraging a frozen DINOv3 backbone and DETR-based detection head to simultaneously perform person detection and multi-label attribute classification via RoIAlign feature extraction.
Duration: January 2026 - Present
- Architected an event-driven Root Cause Analysis (RCA) pipeline triggered by Microsoft's incident management system (IcM) to automate triage for Sev0/Sev1 outages across the IDNA global reverse proxy (routing ~10 trillion daily requests).
- Engineered a Python diagnostic engine leveraging Azure Kusto (KQL) to execute ~100 concurrent time-series anomaly queries across multi-dimensional telemetry, dynamically isolating faults to optimize context windows for an LLM evaluator.
- Backtested the AI agent against historical high-severity incidents, demonstrating a 98% reduction in investigation time (4.5 hours to <5 minutes), and presented architectural findings to drive adoption across adjacent cloud-health teams.
Duration: May 2025 - July 2025
- Engineered a geospatial computer vision pipeline integrating monocular depth estimation and semantic segmentation to project localized road safety hazards onto GIS platforms (ESRI) for North American fleet monitoring.
- Developed a high-precision, two-stage vision pipeline (object detection paired with downstream classification) for automated seatbelt compliance, achieving an F1-score of 0.99 and 97% accuracy across a fleet of 10,000+ commercial vehicles.
- Fine-tuned and optimized an edge-deployed speed-limit sign detector on a custom 15,000-image dataset, achieving 0.88 mAP to ensure real-time compliance tracking in GPS-degraded or map-outdated regions.
Duration: September 2024 - April 2025
- Led technical tutorials and executed rigorous Python code reviews, mentoring students through complex debugging scenarios and foundational software architecture.
Duration: September 2023 - April 2024
AI-powered course scheduler generating conflict-free timetables in <5 mins.
(Typescript, HTML, CSS, Python)
ML pipeline & Data preprocessing tool.
(Python)
Smart AI Assistant.
(OpenAI API, React, Next JS, Firebase, Vercel)
AI powered pantry tracker.
(React, NextJS, Firebase, Vercel, GCP, Gemini API)
Integrated media consumption platform.
(HTML/CSS/JavaScript, Node, Express, SQLite)
You're already there!
(HTML/CSS)
Multithreaded simulation using POSIX threads & semaphores.
(C, Linux, Makefiles, Valgrind)
Classifies seven types of migraines with 93% accuracy.
(Python, TensorFlow, Pandas, Scikit-learn)
💻 Technical skills:
Languages: Python, C/C++, Java
ML / Deep Learning: PyTorch, TensorFlow, Keras, scikit-learn, ONNX, TFLite, OpenCV
ML Ops / Data: Pandas, SQL (MySQL), NoSQL, Kusto (KQL), data labeling & ETL
Cloud / DevOps: AWS, Azure, Docker, Linux, Bash, Git, CI/CD
Focus Areas: Computer Vision, LLM fine-tuning, Prompt Engineering, Model Optimization, Hyperparameter Tuning
🎓 Awards & Honors:
● President’s Faculty Scholarship ($16k)
● Award of Excellence ($5k)
● Dean’s Honor List (2022-2025)
● Vice President & Co-founder @ ColorStackCU
