Job Description
Are you ready to define the moral compass of the next era of technology? FutureScale Inc. is pioneering the frontier of Generative AI, and we are seeking a visionary Lead AI Ethicist to join our elite team in San Francisco.
In a world rapidly transforming by artificial intelligence, the gap between innovation and responsibility is widening. We are looking for a thought leader who can bridge the gap between technical engineering and human values. If you are passionate about ensuring that AI systems are safe, fair, and transparent, this is your opportunity to shape the future of the digital landscape.
As part of our mission to build ethical AI for 2026 and beyond, you will work directly with our Chief Technology Officer and Product Architects to embed ethical considerations into the core of our development lifecycle.
Responsibilities
- Develop and implement comprehensive ethical frameworks for Generative AI models and large-scale machine learning systems.
- Conduct rigorous audits of algorithmic outputs to identify and mitigate bias, discrimination, and harmful societal impacts.
- Collaborate with engineering teams to translate ethical principles into technical specifications and guardrails.
- Lead internal workshops and training sessions to foster a culture of responsibility and awareness across the organization.
- Engage with external stakeholders, policymakers, and academia to contribute to the global discourse on AI safety.
- Monitor emerging global regulations regarding AI ethics and ensure FutureScale Inc. remains compliant and forward-thinking.
Qualifications
- PhD in Philosophy, Computer Science, Law, or a related field (or equivalent extensive professional experience).
- 5+ years of experience in AI ethics, policy, or responsible technology within a tech-focused environment.
- Deep understanding of machine learning concepts, specifically in Natural Language Processing (NLP) and Large Language Models (LLMs).
- Exceptional ability to communicate complex ethical concepts to both technical and non-technical audiences.
- Proven track record of leading cross-functional projects and influencing decision-making processes.
- Familiarity with international standards for AI safety and fairness (e.g., IEEE, OECD guidelines).