Mariko Wakabayashi
ML EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Applied AI Scientist building AI agents for cybersecurity
I'm an engineer experienced with building new AI/ML systems and teams, both in rapidly growing startups and big tech at scale. My current work focuses on applying the latest AI research to build AI agents for cybersecurity. Over the last decade, I’ve enjoyed taking abstract problems from zero to one by building new scalable solutions and teams, often in environments with no prior AI capabilities. My technical background includes: – AI/ML for Security: vulnerability analysis and real-time threat detection – NLP & Deep Learning: productionizing e-commerce content moderation – Scale & Performance: optimizing BERT inference and ML platform performance – Open Source: building scalable solutions and data tools for Project Jupyter My leadership background includes: – Strategy: partnering with execs to define AI roadmaps that create new business value – Team Building: hiring and managing global remote teams across multiple businesses I am happiest when working with a curious and driven team to solve complex technical challenges that create impact in the real world.
University of Illinois Urbana-Champaign
Bachelor of Science (BS), Computer Science
May 1, 2012 – May 1, 2016
Senzoku Gakuen College of Music
High School Diploma, Music Performance
N/A – Present
Microsoft
Principal Applied AI Research Scientist
September 1, 2024 – Present
Firewall
AI Research Lead
November 1, 2023 – August 1, 2024
OpenZeppelin
AI/ML Lead
November 1, 2021 – October 1, 2023
Project Jupyter
Jupyter Server Core Developer (Open Source)
November 1, 2020 – December 1, 2022
Senior Machine Learning Engineer
June 1, 2020 – November 1, 2021
Boulder, Colorado, United States
Bazaarvoice
Staff Machine Learning Engineer
December 1, 2019 – June 1, 2020
Bazaarvoice
Senior Machine Learning Engineer
December 1, 2018 – December 1, 2019
Bazaarvoice
Machine Learning Engineer
October 1, 2017 – December 1, 2018
Addstructure AI
Machine Learning Engineer
October 1, 2017 – February 1, 2018
Chicago, Illinois, United States
Groupon
Software Engineer
July 1, 2016 – October 1, 2017
Chicago, IL
Sensely
Machine Learning Engineer
January 1, 2015 – January 1, 2016
San Francisco Bay Area
University of Illinois at Urbana-Champaign
Research Assistant
April 1, 2014 – May 1, 2015
Urbana-Champaign, Illinois Area
Noshfolio
Software Engineer Intern
January 1, 2014 – January 1, 2015
University of Illinois at Urbana-Champaign
Research Assistant
March 1, 2013 – April 1, 2014
Urbana-Champaign, Illinois Area
Kaggle Competition: detecting phishing scammers on Ethereum
September 1, 2022 – December 1, 2022
I set up and launched a Kaggle competition to invite a broader group of ML contributors to detect phishing scammers on Ethereum. I collected training data from BigQuery and created a tutorial notebook that implements the benchmark model.
Jupyterlab-notifications Lab Extension
January 1, 2021 – Present
Created an open-sourced Jupyterlab extension with 20,000+ installs since March 2021.
State Farm Distracted Driver Detection
January 1, 2016 – February 1, 2016
• Kaggle competition to create a classifier to detect distracted driving behavior. • Created and trained classifier on 22,000+ images to categorize driver behavior in 10 activities using Python, scikit-learn, matplotlib, skimage, and mahotas.
Claude Code: A Highly Agentic Coding Assistant
DeepLearning.AI
June 24, 2026 – Present
Machine Learning Nanodegree
Udacity
June 24, 2026 – Present
Fine-tuning & RL for LLMs: Intro to Post-training
DeepLearning.AI
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from Kaggle competitions to open-source contributions and leadership roles in various companies (Microsoft, Firewall, OpenZeppelin, Twitter, Bazaarvoice), indicates a strong adaptability and a broad interest in applying ML across different domains. Their experience in both established tech giants and startups, coupled with a focus on real-world problem-solving (e.g., detecting exploits, optimizing ML infrastructure, e-commerce moderation), suggests a pragmatic and impact-driven approach. The target role of ML Engineer aligns well with their extensive experience in ML system design, deployment, and research, particularly in security and AI agents.
Soft Skills & Operational Fit
The candidate's resume demonstrates strong leadership, project ownership, and cross-functional collaboration skills, particularly in leading AI/ML teams and initiatives. Their involvement in open-source projects and Kaggle competitions also suggests a proactive and collaborative work attitude. The descriptions indicate an ability to drive projects from conception to deployment, including data collection, model development, and API creation. The lack of psychometric test results prevents a direct assessment of logical reasoning, stress handling, or team collaboration under pressure.