Job
Description
Job Description : As a Security, Safety, Privacy, Regulatory Engineer for our Large Language Model Project, you will be a key player in ensuring the robustness, compliance, and ethical use of our language models. Your role will involve implementing and overseeing security measures, addressing safety considerations, safeguarding user privacy, and ensuring compliance with relevant regulations and standards. This position is critical in establishing trust and mitigating risks associated with the deployment of large language models. Key Responsibilities : Security Implementation - Design and implement security measures to safeguard against potential threats, vulnerabilities, and unauthorized access to language models. Conduct regular security audits and assessments, collaborating with cybersecurity experts to enhance model security. Safety Protocols - Develop and implement safety protocols to identify and mitigate risks associated with language model deployment, including potential biases and unintended consequences. Work closely with the development team to address safety concerns and ensure responsible AI practices. Privacy Protection - Establish and enforce privacy controls to protect user data and ensure compliance with privacy regulations. Conduct privacy impact assessments and work with legal and compliance teams to address privacy-related concerns. Regulatory Compliance - Stay abreast of relevant laws, regulations, and industry standards related to AI, language models, and data processing. Ensure that language models adhere to all applicable regulatory requirements and work towards obtaining necessary certifications. Ethical Considerations - Advocate for ethical AI practices and contribute to the development of guidelines for responsible and fair use of language models. Collaborate with cross-functional teams to address ethical concerns and implement transparency measures. Skills & Tools Security Tools - Familiarity with security tools and frameworks such as Nessus, Metasploit and OWASP ZAP for vulnerability assessments, penetration testing, and threat modeling. Familiarity with secure development tools such as SonarQube, Checkmarx, or Fortify for identifying and mitigating security vulnerabilities in software code. Encryption Technologies - Knowledge of encryption technologies and tools like OpenSSL, VeraCrypt, or AWS Key Management Service (KMS) for data encryption at rest and in transit. Compliance Frameworks - Knowledge of relevant compliance frameworks, such as GDPR, HIPAA, and others, and experience in implementing compliance measures using OneTrust & Trustarc. Privacy Impact Assessment Tools - Experience with tools and methodologies for conducting privacy impact assessments and ensuring compliance with privacy regulations. Regulatory Knowledge - Understanding of AI-related regulations, standards, and guidelines, and the ability to interpret and implement them in the context of language models. Knowledge of privacy-enhancing technologies such as homomorphic encryption, differential privacy, and secure multi-party computation, and experience in their practical implementation.
