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Information Technology 🏢 Full Time ⭐️ Verified

2026 AI Strategy Lead

FutureVision Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

Shape the future at FutureVision Labs as our 2026 AI Strategy Lead. We're seeking a visionary leader to architect next-generation AI frameworks that will redefine human-machine collaboration. Join an elite team pioneering ethical AI solutions for autonomous systems, predictive analytics, and quantum-optimized neural networks. Your work will directly influence how industries leverage AI by 2026, from climate modeling to personalized healthcare. Enjoy competitive equity, unlimited PTO, and a state-of-the-art lab in San Francisco's tech corridor.

Responsibilities

  • Develop comprehensive 2026 AI roadmaps aligned with industry disruption forecasts
  • Lead cross-functional teams in prototyping quantum-resistant AI algorithms
  • Establish governance frameworks for ethical AI deployment in high-stakes sectors
  • Forge strategic partnerships with academic institutions and Fortune 500 innovators
  • Present AI strategy to C-suite executives and government technology councils
  • Drive R&D initiatives for neuromorphic computing applications
  • Mentor junior researchers on emerging AI paradigms and regulatory landscapes

Qualifications

  • PhD in Computer Science/AI or equivalent with 8+ years in applied AI research
  • Proven track record deploying production AI systems in regulated industries
  • Expertise in federated learning, explainable AI (XAI), and adversarial machine learning
  • Deep understanding of quantum computing principles and their AI applications
  • Published research in top-tier AI/ML conferences (NeurIPS, ICML, ICLR)
  • Experience leading AI ethics initiatives with measurable impact
  • Strong proficiency in Python, TensorFlow/PyTorch, and cloud ML platforms

Required Skills

AI Strategy Quantum Computing Federated Learning Explainable AI Neuromorphic Computing TensorFlow Ethics in AI Cloud ML

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