Job Description
We are standing at the precipice of the next major leap in human history. Quantum Horizon AI is building the Artificial General Intelligence (AGI) systems of 2026, and we need a visionary leader to ensure these systems align with the best of humanity.
This is a unique opportunity for a researcher, philosopher, and engineer to define the ethical guardrails for the most powerful technology ever created. You won't just be auditing code; you will be crafting the moral architecture of the future.
Why Join Us?
- Impact First: Your work will directly influence the safety and deployment of AGI systems affecting billions.
- The 2026 Vision: Work in a cutting-edge environment focused on long-term AI safety and existential risk mitigation.
- Top-Tier Talent: Collaborate with the brightest minds in AI safety, cognitive science, and policy.
Our Mission
To ensure that the emergence of AGI leads to a prosperous, safe, and equitable future for all.
Responsibilities
- Define Alignment Frameworks: Develop rigorous mathematical and philosophical frameworks to ensure AGI systems act in accordance with human values and safety constraints.
- Risk Assessment: Conduct comprehensive risk analysis on emerging AI architectures to identify potential vulnerabilities and misalignment risks.
- Policy Development: Create and implement internal safety protocols and ethical guidelines for the engineering and research teams.
- Interdisciplinary Collaboration: Partner with machine learning researchers, engineers, and external academic institutions to align research agendas.
- Technical Advisory: Serve as the primary advisor to the CTO and Board of Directors on AI safety and ethical implications.
- Research Publication: Author white papers and contribute to the global academic discourse on AI safety and alignment.
Qualifications
- Education: PhD, Master’s, or equivalent experience in Computer Science, Philosophy, Ethics, Cognitive Science, or a related quantitative field.
- Experience: 5+ years of experience in AI research, machine learning engineering, or AI safety research.
- Technical Fluency: Deep understanding of machine learning concepts (transformers, RLHF, reinforcement learning) and their potential failure modes.
- Reasoning Skills: Exceptional ability to think abstractly and reason about complex systems, including counterfactual reasoning and game theory.
- Communication: Proven ability to communicate complex technical and philosophical concepts to diverse audiences, including non-technical stakeholders.
- Vision: Demonstrated passion for the long-term future of AI and a proactive approach to solving existential risks.