AI Security Expert

🕒 May 11

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Pear Tree.

WebsiteLinkedInAll Job Openings

1 - 10 employees

🎯 Recruiter

👥 HR Tech

🤝 B2B

Recruitment • HR Tech • B2B

Pear Tree is a Melbourne‑born offshore recruitment and hiring services company that connects Australian, US, and UK businesses directly with skilled offshore professionals (primarily from the Philippines) without agency markups. They provide end-to-end hiring support — sourcing, screening, skills assessments, video interviews, reference checks — and offer payroll, Employer‑of‑Record, and compliance assistance plus a six‑month replacement guarantee. Pear Tree recruits across IT, sales & marketing, finance, creative, admin and operations roles, emphasizing cost savings, direct pay to talent, and secure onboarding workflows.

📋 Description

• Pipeline Security: Designing and implementing protocols to secure model training and deployment pipelines against unauthorized access or tampering. • Adversarial Defense: Proactively identifying and preventing adversarial attacks, including input manipulation, model inversion, and data poisoning. • Intellectual Property & Privacy: Implementing advanced measures to protect sensitive dataset privacy and safeguard our proprietary model intellectual property. • Threat Modeling & Red Teaming: Conducting AI-specific threat modeling and internal "red team" exercises to discover vulnerabilities before they can be exploited. • Governance & Compliance: Ensuring all AI initiatives align with global security standards (e.g., ISO/IEC 42001, NIST AI RMF), ethical guidelines, and emerging AI governance frameworks.

🎯 Requirements

• AI/ML Proficiency: Strong understanding of machine learning frameworks (e.g., PyTorch, TensorFlow) and the underlying mathematics of model architectures. • Adversarial AI Knowledge: Proven experience with adversarial machine learning techniques, such as Gradient-based attacks, Evasion attacks, and Model Extraction. • Secure Software Development: Expertise in securing CI/CD pipelines and containerized environments (Docker, Kubernetes) specifically for ML workloads. • Data Protection: Proficiency in privacy-preserving technologies such as Differential Privacy, Homomorphic Encryption, or Federated Learning. • Cloud Security: Deep experience with security configurations in AWS, Azure, or GCP, specifically regarding managed AI services (e.g., SageMaker, Vertex AI). • Education: A Bachelor’s or Master’s degree in Computer Science, Cybersecurity, Data Science, or a related field. • Professional Background: 5+ years of experience in Cybersecurity, with at least 2 years specifically focused on AI/ML security or research. • Certifications: Relevant certifications such as CISSP, CISM, or specialized AI certifications (e.g., Certified AI Security Professional) are highly regarded.