Machine Learning Engineer (AI Security)

Location: Cairo, Egypt

Salary: $36,000–$60,000 per year, determined based on location, qualifications, experience, and relevant skills.

Company

hirify.global develops intent-based AI security products that detect jailbreaks, data exfiltration, shadow AI, and other risks in AI usage.

What you will do

• Build scalable pipelines for collecting, preprocessing, and managing datasets used to train and evaluate large language models.
• Design and run experiments measuring model accuracy, robustness, fairness, and safety.
• Create dashboards, reports, and visualizations covering evaluation results, trends, and failure cases.
• Develop knowledge graphs to structure data, enrich evaluation, and improve context-driven model performance.
• Collaborate with researchers and data scientists to turn new ideas into engineering workflows, automated QA checks, and guardrails.
• Fine-tune, optimize, monitor, and integrate models into production systems while applying CI/CD and scalability best practices.

Requirements

• 2–5+ years of experience in machine learning or data science.
• Strong software engineering skills with Python, testing frameworks such as pytest or unittest, and CI/CD tools.
• Proficiency with PyTorch and strong knowledge of supervised and unsupervised learning, deep learning, and NLP.
• Experience with data engineering tools such as Spark, Kafka, or Airflow.
• Experience deploying models on AWS, GCP, or Azure and working with Docker and Kubernetes.
• Interest or experience in cybersecurity, adversarial machine learning, anomaly detection, model robustness, or explainable AI.

Nice to have

• Experience building interactive dashboards for model monitoring and visualization.
• Contributions to open-source machine learning, NLP, or security projects.
• Experience in a security- or infrastructure-heavy environment.

Culture & Benefits

• Fast-moving startup environment focused on shipping and rapid iteration.
• Opportunity to work across applied research, machine learning engineering, and AI security.
• Focus on building reliable, interpretable, and safe language models for production use.