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Information Technology 🏢 Full Time ⭐️ Verified

AI Futurist Research Lead

Quantum Leap Dynamics
San Francisco
Estimated Salary
USD 220.000 – USD 300.000
New
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Join Quantum Leap Dynamics at the forefront of 2026's technological revolution. We're seeking visionary AI Futurist Research Leads to architect next-generation intelligence systems that will redefine human-machine collaboration. This role blends cutting-edge machine learning with ethical foresight to shape solutions for climate modeling, quantum computing interfaces, and autonomous ecosystem management.

What you'll impact: Lead interdisciplinary teams in developing predictive AI frameworks that solve 2026's most complex challenges. Your work will directly influence global sustainability initiatives and next-generation human augmentation technologies. We offer unparalleled resources, flexible innovation time, and collaboration with Nobel laureate advisors.

Responsibilities

  • Architect ethical AI governance frameworks for 2026's autonomous systems
  • Lead cross-functional R&D teams in quantum-ML integration projects
  • Develop predictive models for climate-positive industrial optimization
  • Design neural interfaces for human-AI symbiosis applications
  • Pioneer generative AI systems for synthetic biology breakthroughs
  • Present findings at global tech summits and peer-reviewed journals
  • Mentor junior researchers in emerging AI safety protocols

Qualifications

  • PhD in Computer Science/AI or equivalent with 5+ years research leadership
  • Published work in top-tier ML conferences (NeurIPS, ICML)
  • Expertise in quantum machine learning and neuromorphic computing
  • Proven track record in ethical AI framework development
  • Experience with large-scale distributed ML infrastructure (Kubernetes, Spark)
  • Strong background in predictive modeling for complex systems
  • Deep understanding of 2026 technological landscape and regulatory trends

Required Skills

AI Ethics Quantum Computing Machine Learning Predictive Modeling Neuromorphic Systems Distributed Computing Climate AI Human-AI Interaction

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