AI Security Engineer

Company Overview:

At Machine Learning Reply, we provide cutting-edge consulting services at the intersection of AI and cybersecurity. Our team of experts helps businesses protect their AI-driven systems, data pipelines, and cloud infrastructures from evolving security threats. We are passionate about making AI safer, more ethical, and more resilient for companies across industries. As we continue to expand, we’re looking for a skilled AI Security Engineer to join our consulting team and deliver security solutions to our clients.

Job Description:

We are seeking a talented and experienced AI Security Engineer to join our consulting firm. You will work directly with clients to evaluate, design, and implement security solutions that protect their AI systems, machine learning models, and data infrastructure. In this role, you’ll take the lead on advising companies on best security practices, mitigating AI-specific risks, and ensuring the compliance of AI systems with security regulations. Your work will involve close collaboration with clients' AI and IT teams to create secure AI infrastructures, resilient to cyber threats and adversarial attacks.

Responsibilities:

• Consult and advise clients on best practices for securing AI systems, data pipelines, and IT infrastructure.
• Conduct security assessments and audits on AI models, identifying potential vulnerabilities such as adversarial threats and model inversion attacks.
• Develop and implement security strategies for AI-driven systems that comply with industry regulations and ethical standards.
• Assist clients in designing secure data pipelines, ensuring the integrity, confidentiality, and availability of AI-related data.
• Perform threat modeling and risk assessments, with a focus on AI-specific vulnerabilities and ethical risks.
• Help clients mitigate risks of data poisoning, bias exploitation, and adversarial attacks on machine learning models.
• Implement and maintain security protocols like access control, encryption, and anomaly detection tailored for AI applications.
• Research and recommend emerging AI security tools to enhance clients' security postures.
• Educate and train client teams on the evolving landscape of AI security, ensuring knowledge transfer and internal capacity-building.
• Collaborate with the internal consulting team to deliver end-to-end security solutions, from design to execution and post-implementation support.
• Respond to client-specific security incidents involving AI systems and provide recovery strategies.

Requirements

Qualifications:

Education:

• Bachelor’s or Master’s degree in Cybersecurity, Computer Science, IT, or a related field.
• Certifications in security (e.g., CISSP, CEH, Security+) or relevant AI certifications are a plus.

Experience:

• 3+ years of experience in IT security, with 1-2 years in AI/ML-related projects.
• Experience in consulting, including client-facing roles where you delivered IT or security solutions.
• Strong knowledge of AI frameworks and platforms such as TensorFlow, PyTorch, or Scikit-learn, and their security challenges.
• Familiarity with cloud security in AI environments (AWS, Azure, or GCP), with a focus on securing machine learning workloads.
• Experience in security assessments, vulnerability management, and incident response, particularly within AI contexts.

Useful Skills:

1. Cybersecurity Skills:
   • Deep understanding of network security, firewalls, IDS/IPS, and encryption techniques.
   • Strong knowledge of data security protocols, secure access control, and multi-factor authentication.
   • Expertise in SIEM systems and security monitoring tools (e.g., Splunk, ELK Stack).
   • Experience with penetration testing and securing distributed AI models and APIs.
2. AI-Specific Security Skills:
   • Experience with adversarial machine learning techniques (e.g., model evasion, poisoning, and data inference attacks).
   • Knowledge of AI model auditing for bias, fairness, and transparency.
   • Familiarity with differential privacy, federated learning, and other privacy-preserving AI techniques.
   • Understanding of the ethical implications of AI security, including governance frameworks like the EU AI Act and GDPR.
   • Expertise in securing data pipelines used for training machine learning models, including data anonymization and encryption.
3. Consulting & Client Management:
   • Strong interpersonal skills with the ability to engage effectively with clients at various technical levels.
   • Proven track record of delivering tailored solutions that address client-specific security challenges.
   • Ability to clearly communicate technical security issues and solutions to non-technical client stakeholders.
   • Experience working with cross-functional teams, especially with AI and data science teams, to ensure security alignment.
4. Technical Proficiency:
   • Proficiency in Python, Java, or C++, particularly in the context of AI and cybersecurity.
   • Knowledge of security tools specific to AI, such as IBM’s Adversarial Robustness Toolbox, CleverHans, or SecML.
   • Experience in container security (e.g., Docker, Kubernetes) and cloud security solutions (e.g., AWS KMS, Azure Key Vault).
   • Familiarity with blockchain technologies for secure data exchanges and decentralized AI computations is a plus.
5. Continuous Learning:
   • A commitment to staying ahead of the curve on new developments in both cybersecurity and AI.
   • Willingness to adapt quickly to changing client needs and emerging threats in the AI security landscape.

Technologies:

• AI/ML Security Tools:
  • Adversarial defense frameworks (e.g., Adversarial Robustness Toolbox, Foolbox)
  • Model security frameworks (e.g., CleverHans, SecML)
  • Explainability and fairness tools (e.g., SHAP, LIME, Fairness Indicators)
• Cloud Security Tools:
  • Cloud Security Posture Management (CSPM) platforms (e.g., Prisma Cloud, Lacework)
  • Cloud-native encryption tools (e.g., AWS KMS, Google Cloud KMS)
• Data Security:
  • Federated learning platforms (e.g., TensorFlow Federated, PySyft)
  • Privacy-preserving AI techniques such as differential privacy and secure multi-party computation (MPC).

Bonus Skills:

• Understanding and expertise on the EU AI Act
• Familiarity with zero-trust architectures for AI systems.
• Experience with blockchain technologies applied to AI security.

Perks and Benefits:

• Opportunity to work with diverse clients across multiple industries.
• Competitive salary and performance bonuses.
• Choice of the hardware between MacBooks/Windows and iPhones/Android.
• Access to cutting-edge AI security technologies.
• Professional development and continuous learning opportunities.
• Flexible work arrangements.