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2026 AI Research Lead

QuantumLeap Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
3 Juni 2026
Deadline
3 Jun 2027

Job Description

Join QuantumLeap Dynamics at the forefront of technological innovation as we pioneer the next generation of AI systems. We're seeking a visionary 2026 AI Research Lead to architect transformative solutions that will redefine human-machine collaboration. In this pivotal role, you'll lead a multidisciplinary team in developing cutting-edge neural networks and quantum-inspired algorithms. You'll collaborate with industry disruptors to solve complex challenges in healthcare, climate modeling, and autonomous systems. Our culture embraces radical experimentation and rewards bold innovation. If you're passionate about shaping the future of artificial intelligence, this is your moment to make history.

Responsibilities

  • Architect and execute advanced AI research roadmaps targeting 2026 technological milestones
  • Lead a team of 8+ researchers in developing novel neural network architectures
  • Collaborate with quantum computing specialists to create hybrid AI solutions
  • Translate research breakthroughs into scalable production-ready systems
  • Publish findings in top-tier journals and present at global tech conferences
  • Secure $5M+ in annual research funding through strategic partnerships
  • Mentor PhD-level researchers and foster a culture of intellectual curiosity
  • Drive ethical AI frameworks that align with UN Sustainable Development Goals

Qualifications

  • PhD in Computer Science, AI, or a related field with 8+ years of research experience
  • Proven track record of publishing in NeurIPS, ICML, or Nature Machine Intelligence
  • Expertise in transformer architectures, reinforcement learning, and federated learning
  • Experience leading cross-functional teams of 10+ researchers
  • Demonstrated ability to secure $3M+ in research funding
  • Strong background in quantum computing principles and their AI applications
  • Published work on ethical AI frameworks or bias mitigation techniques
  • Experience scaling ML systems to handle petabyte-scale datasets

Required Skills

Neural Networks Quantum Computing Reinforcement Learning Transformer Architecture Federated Learning AI Ethics Research Leadership Large-Scale ML Systems

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