About Charlemagne Labs

Charlemagne Labs is building the first Human Digital Hygiene platform—an intelligent, on-device safety agent ("Agent Charley") that prevents humans from making costly cybersecurity mistakes. Our mission is to defend individuals and organizations against the new wave of agentic, AI-driven social engineering threats. We're combining cutting-edge small language models (SLMs), privacy-first system design, and HCI research to create proactive, zero-egress defenses that stop bad clicks before they happen.

Role Overview

We're looking for an AI Engineer who's excited to work at the intersection of applied machine learning and cybersecurity. You'll help fine-tune and evaluate local LLMs that detect, reason about, and intervene in risky human-computer interactions (e.g., phishing, spoofed sign-in pages, or malicious URLs). You don't need a background in cybersecurity—but curiosity about the threat landscape, adversarial behavior, or human error is a big plus. We are looking to hire immediately and move quickly for the right candidate.

Responsibilities

Fine-tune open-source language models (Gemma, LLaMA, Mistral, Qwen, etc.) for domain-specific reasoning about browser-based risk
Build and maintain pipelines for dataset preparation, tokenization, supervised fine-tuning (SFT), and evaluation
Experiment with parameter-efficient techniques (LoRA, QLoRA, or adapters) for small-device deployment
Contribute to labeling, prompt engineering, and evaluation of threat detection capabilities (e.g., phishing intent or anomaly detection)
Develop safety classifiers or scoring systems that map model reasoning to user-facing confidence levels or 'amber alert' thresholds
Collaborate on experiments studying local inference, hallucination reduction, and privacy-preserving architectures (e.g., zero-egress LLM operation)
Integrate the SLM into browser extensions and local agents
Build and maintain training datasets reflecting realistic user interactions and cyberattack patterns
Implement and monitor model performance metrics and contribute to model interpretability research

Preferred Qualifications

Bachelor's degree in Computer Science, Data Science, or related field, or equivalent experience
Hands-on experience with Python, PyTorch, and Hugging Face Transformers
Experience with model fine-tuning or instruction-tuning workflows
Familiarity with LLM evaluation metrics and prompt engineering
Interest in cybersecurity domains such as phishing, anomaly detection, or malware classification (optional)
Interest in AI safety, privacy-preserving ML, or human-computer interaction for cybersecurity

What You'll Learn

How small, local LLMs can power real-time cybersecurity defense. How to apply AI reasoning to detect and interrupt advanced social engineering attacks. How agentic AI systems are reshaping both offensive and defensive cyber operations. Startup-level productization of research: moving from proof-of-concept to deployed, safety-critical software.

Why Join Us

You'll be joining a small, mission-driven team of builders from Meta, DoD, and cybersecurity research who are reimagining digital safety for the era of agentic AI. You'll work directly with our founder and lead engineer, contribute to published research, and help define a new category: Human Digital Hygiene.

Charlemagne Labs, Inc. AI Jobs

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