Software Engineer & ML Researcher

KenWu.

吴锵皓
Based inWaterloo, ON
EducationUniversity of Waterloo, CS '26
StatusSeeking Fall 2026 / New Grad — ML, Systems, SWE
GitHubLinkedInEmailResumeX
Neo Scholar Finalist◆5x Hackathon Winner◆Stanford Code in Place Instructor◆Undergraduate Research Assistant◆Research Exchange — Lancaster University
七7
Internships
五5
Hackathon Wins
四4
Countries
人
素顔 — Beyond Code

Beyond Code

🇮🇹Born―🇨🇳Raised―🇨🇦Studying―🇺🇸Interned―🇬🇧Exchanged
球NBA

Fine-tuned an LLM on r/nba posts. Built an AI that roasts bad basketball takes on X.

将Chess

Mediocre player. Builds chess bots on the side to compensate.

哲Philosophy

Minor who thinks about AI alignment when not shipping ML pipelines.

余Off-duty

Basketball, poker, anime, and the occasional Leetcode grind.

経験
経験 — Experience

Experience

一

Nokia

Software Engineer Intern5G Network AgentJul 2025 — Dec 2025Ottawa, Canada
  • —Built LoRA fine-tuning pipeline for Qwen generating Camunda BPMN XML with GGUF quantization
  • —Designed evaluation framework revealing overfitting from NCSC-only data vs. base models
  • —Resolved GPU memory and Triton issues and shipped reusable training tooling for future experiments
Python·PyTorch·Unsloth·Transformer
二

TD Bank

Data Scientist InternInsurance AnalysisJun 2025 — Aug 2025Toronto, Canada
  • —Replatformed pipelines for 1.5M+ rows of data and reproduced a 154,340 row deliverable with 100% parity
  • —Automated 30+ minutes of manual ingestion per cycle, cutting QA time by 80% via a parity harness
  • —Migrated on-prem pipeline to Azure fully automating runs and saving 2–4 hours/week of manual execution
Python·SQL·PySpark·Pandas·Databricks
三

Stanford University

Student InstructorTeachingApr 2025 — Jun 2025Stanford, United States
  • —Taught Stanford’s Code in Place CS106A course to students globally, taken by 40,000+ students
  • —Educated students in Python leveraging beginner friendly libraries including Stanford’s Karel and Tkinter
Python·Karel·Tkinter
四

August

Software Engineer InternLLM AgentSept 2024 — Dec 2024New York, United States
  • —Handled 2,000+ requests/min by deploying 10+ API endpoints using FastAPI, AWS, and Supabase
  • —Optimized evaluation cycles for 15+ LLM Agents with a round-robin multi-agent and scoring framework
  • —Led the end-to-end development of a multi-agent RAG pipeline powered by LLM-as-Judge strategies
Python·LangGraph·FastAPI·AWS
五

Health Canada

Machine Learning Engineer InternDocument QAApr 2024 — Aug 2024Ottawa, Canada
  • —Built a document QA system using Llama3 7B and ChromaDB for OECD report search and summarization
  • —Increased response and semantic accuracy by ~20% using query transformation and contextual memory
Python·Azure·LangChain·Streamlit
六

Keywords AI

Y Combinator W24
Software Engineer InternResume ParsingMar 2023 — Jun 2023New York, United States
  • —Parsed 1,000+ resumes with a spaCy-based NER pipeline to extract structured recruiter data
  • —Reduced response delay by 98% through integration of SQLite-based result caching into the parsing engine
Python·spaCy·SQLite
七

Intapp

Formerly delphai
Machine Learning Engineer InternEntity RecognitionJul 2022 — Sept 2022Berlin, Germany
  • —Boosted recall by 20% through improved entity labeling workflows and language-specific training sets
  • —Achieved 70% recall by fine-tuning spaCy models and optimizing hyperparameters via WanDB on Azure
Python·spaCy·W&B·BS4
作品
作品 — Projects

Projects

一

Ding-Bot

Chess engine combining GATEAU-style Graph Attention Networks with contrastive latent-space search

Python·TypeScript·Graph Neural Networks
Source
二

PokerMon

Deep Counterfactual Regret Minimization (Deep CFR) for 6-player No-Limit Texas Hold'em

Python·Deep CFR·Game Theory
Source
三

LeGM-Lab

AI-powered NBA take analyzer that fact-checks basketball opinions with real stats and roasts bad takes on X

Python·Claude API·FastAPI·X API
SourceLive
四

LeLM

Fine-tuned LLM for NBA hot takes, built on Qwen3-8B with LoRA and trained on Reddit r/nba posts

Python·Unsloth·LoRA·Hugging Face
Source
五

Algoherence

18 stars

Stock trading chatbot democratizing financial literacy with RAG-powered advice and live Alpaca paper trading

Python·LangChain·Cohere·Streamlit
Source
六

OpenFintech

Financial analysis library for trend following and mean reversion strategies, built for Python developers and analysts

Python·Fintech·Open Source
Source
技術
技術 — Skills

Skills

Languages
言語Languages
Python/SQL/C/C++/TypeScript/JavaScript/HTML/CSS/R/Racket/Bash
Technologies & Cloud
技術Technologies & Cloud
PySpark/NumPy/Pandas/spaCy/MongoDB/Supabase/PostgreSQL/AWS/Docker/Git
Libraries & Frameworks
枠組Libraries & Frameworks
PyTorch/LangChain/Flask/FastAPI/TensorFlow/Keras/CUDA/React/Next.js/Tailwind
繋
連絡 — Contact

Let's build something together.

ken.wu@uwaterloo.ca
GitHubLinkedInResumeX

Ken Wu

2026