harkous@home:~$  Hamza Harkous

• Founder & Lead, Simula Framework: Co-founded and grew Google's internal leading synthetic data framework (with total of 2 tech FTEs) to serve 450 monthly active Googlers (>1k unique users in 2025). Enabled the generation of >1 billion data items while achieving the highest satisfaction score (93%) across all Google data tools.
• Creator, Simula Agent: Built the most widely used internal data-generation agent (since 2024). Currently serving >200 monthly active users, the agent auto-generates hundreds of end-to-end Colabs per month, specialized for Googlers' data generation needs.
• Gemma Ecosystem: Simula served as a primary data engine for the Gemma family, including the upcoming Gemma models, ShieldGemma, FunctionGemma, and MedGemma.
• Gemini Ecosystem: The framework contributed to frontier model development and safety:
  • Safety & Security: Powering all safety classifiers (server-side & on-device); contributed to Cybersecurity, Red-Teaming, and Prompt Injection defenses.
  • Distillation & Features: Supporting Gemini Flash Lite distillation, Nano (e.g., i18n post-training), and Gemini app features.
  • Evaluations: Enabled evaluations in specialized Gemini verticals.
• Wider Impact: Instrumental in public launches, such as Android Call Scam and Messages Spam detection. The framework is also integrated into Vertex AI's GenAI Evaluation Service.

Nov 2021 – Oct 2023

Senior Research Scientist, Google

• Founder, Internal Data-Curation Platform: Bootstrapped an internal web platform combining diversified retrieval, active learning, and LLM assistance. I grew the contributing team to 13 engineers, evolving the project into a foundational data engine for numerous modeling initiatives.
• ML Lead & Architect, Google Checks: Continued to lead the ML strategy for Google's AI-powered privacy compliance platform, scaling the models to secure thousands of mobile apps.

Feb 2020 – Oct 2021

Research Scientist, Google

• ML Architect, Google Checks: Architected the initial ML models for Google's privacy compliance platform. I designed the entire ML pipeline, including data labeling, model pre-training, and distillation.
• Lead Researcher & Developer, Hark: Built the core ML models and infrastructure for a large-scale privacy-feedback analytics system used daily by 300+ triagers and processing tens of millions of reviews.

Jul 2019 – Jan 2020

Applied Scientist, Amazon Alexa

Developed DATATUNER, a neural data-to-text generation system with state-of-the-art semantic fidelity.

Nov 2018 – May 2019

Machine-Learning & Privacy Consultant, Privately SA

Shipped on-device classifiers for hate-speech, toxicity, and emotion detection; technology launched in a BBC-branded mobile keyboard.

Jul 2017 – Sep 2018

Post-doctoral Researcher, EPFL (LSIR-Lab)

Lead author and developer of Polisis, an AI tool that analyzed privacy policies for >45,000 users. The project was featured in major publications like Wired and WSJ.