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Information Technology 🏢 Full Time ⭐️ Verified

2026 AI Strategy Lead

QuantumLeap Industries
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
20 Mei 2026
Deadline
20 Mei 2027

Job Description

Join QuantumLeap Industries at the forefront of technological evolution as we shape the future of AI-driven innovation. As the 2026 AI Strategy Lead, you'll architect the next generation of autonomous systems that will redefine industries by 2026. This pivotal role demands visionary leadership and technical expertise to transform cutting-edge research into scalable solutions.

We offer unparalleled opportunities to work with Nobel laureates and patent-pending technologies in our state-of-the-art San Francisco R&D center. Your impact will directly influence global AI adoption across healthcare, climate tech, and autonomous infrastructure.

Responsibilities

  • Develop and execute the 2026 AI roadmap, aligning with global sustainability initiatives
  • Lead cross-functional teams of ML researchers and engineers to prototype breakthrough AI models
  • Drive strategic partnerships with academia and government for quantum-AI integration
  • Architect ethical AI frameworks ensuring compliance with 2026 global AI governance standards
  • Present findings to C-suite and industry consortiums at annual FutureTech Summit
  • Mentor junior talent through our AI Innovation Fellowship program

Qualifications

  • PhD in Machine Learning, Computer Science, or related field with 8+ years industry experience
  • Proven track record deploying production-grade AI systems (LLMs, reinforcement learning)
  • Expertise in quantum computing algorithms and federated learning architectures
  • Published research at NeurIPS/ICML with 50+ citations in AI ethics domain
  • Proficiency in PyTorch, TensorFlow, and quantum computing frameworks
  • Fluency in regulatory frameworks (EU AI Act, US AI Bill of Rights)

Required Skills

Artificial Intelligence Machine Learning Quantum Computing Strategic Planning AI Ethics Research Leadership PyTorch TensorFlow

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