Job Description
We are seeking a visionary AI Ethics & Governance Architect to lead our mission in deploying safe, responsible, and transparent artificial intelligence systems. As we prepare for the next generation of machine learning deployment in 2026, you will be at the forefront of defining the ethical frameworks that guide our technology.
In this pivotal role, you will collaborate with engineering, legal, and product teams to integrate ethical considerations into the core of our AI development lifecycle. If you are passionate about the intersection of technology, philosophy, and policy, we want to hear from you.
Responsibilities
- Develop Ethical Frameworks: Create and maintain comprehensive guidelines for the ethical use of AI, focusing on bias mitigation, fairness, and transparency in neural network models.
- Algorithmic Auditing: Conduct rigorous audits of our AI systems to ensure compliance with emerging regulations and industry standards for responsible AI.
- Stakeholder Collaboration: Work closely with data scientists and software engineers to translate ethical principles into technical requirements and code constraints.
- Risk Assessment: Identify potential societal and safety risks associated with emerging AI technologies and propose mitigation strategies.
- Policy Development: Stay ahead of global regulatory trends (e.g., EU AI Act, US Executive Orders) and advise leadership on necessary policy adjustments.
- Education & Training: Conduct workshops and training sessions for technical teams to foster a culture of ethical awareness and responsibility.
Qualifications
- Education: Master’s or PhD in Computer Science, Ethics, Philosophy, Law, or a related field.
- Experience: 5+ years of experience in AI/ML development, data science, or a related technical field with a strong focus on AI safety.
- Technical Proficiency: Deep understanding of machine learning algorithms, large language models (LLMs), and generative AI architectures.
- Analytical Skills: Proven ability to analyze complex datasets and identify potential biases or ethical pitfalls in AI models.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Regulatory Knowledge: Familiarity with current and proposed AI regulations and governance frameworks.