AI/ML Security Specialists

Role Summary The AIML Security Specialist will secure AIML model deployment, develop security frameworks for machine learning systems, and monitor AIspecific threats. This role addresses the emerging risks associated with AI technologies. Job Description Securing AIML pipelines from the development phase through to production, including the implementation of safeguards against model poisoning and adversarial attacks. Conducting risk assessments on AI models, ensuring that privacypreserving techniques such as federated learning and homomorphic encryption are integrated where necessary. Developing comprehensive security frameworks for machine learning algorithms, including guidelines for securing datasets, managing model biases, and ensuring robustness against adversarial inputs. Incorporating best practices for protecting model integrity from data breaches, using techniques such as watermarking and model fingerprinting. Monitoring AIML model behaviour postdeployment for any signs of adversarial activity, such as input manipulation or model degradation. Incident Response and Forensic Analysis of Telecom Nodes to Conduct Compromise Assessment Threat Hunting.Desired Candidate Profile We are looking for talented AIML Security Specialists to join our cybersecurity team. The ideal candidates should have a strong background in artificial intelligence AI and machine learning ML technologies, with a focus on security applications. Indepth knowledge of AIML algorithms and frameworks, such as Tensor Flow, scikitlearn, or Py Torch, is essential. Candidates should demonstrate expertise in identifying and mitigating security risks in AIML systems, including model poisoning, adversarial attacks, and data privacy concerns. Experience in implementing security measures, such as encryption, authentication, and access control, within AIML environments is highly desirable. The ability to conduct vulnerability assessments and penetration testing on AIML models is crucial to ensuring their resilience against cyber threats. Candidates must stay abreast of emerging threats and security trends in the AIML landscape and proactively recommend and implement security best practices. Effective communication skills and the ability to collaborate with crossfunctional teams, including data scientists and cybersecurity experts, are key to success in this role. Requirements Strong background in AI and ML technologies. Knowledge of AIML algorithms and frameworks Tensor Flow, scikitlearn, Py Torch. Expertise in identifying and mitigating security risks in AIML systems. Experience in implementing security measures within AIML environments. Ability to conduct vulnerability assessments and penetration testing on AIML models. Knowledge of emerging threats and security trends in the AIML landscape. Effective communication and collaboration skills. Proactive approach to recommending and implementing security best practices.Disclaimer: Naukrigulf.com is only a platform to bring jobseekers & employers together. Applicants are advised to research the bonafides of the prospective employer independently. We do NOT endorse any requests for money payments and strictly advice against sharing personal or bank related information. We also recommend you visit Security Advice for more information. If you suspect any fraud or malpractice, email us at abuse@naukrigulf.com #J-18808-Ljbffr