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AI Research Lead 2026

QuantumLeap Dynamics
San Francisco
Estimated Salary
USD 185.000 – USD 275.000
Live Update
11 Mei 2026
Deadline
11 Mei 2027

Job Description

Join QuantumLeap Dynamics at the forefront of 2026's technological revolution. We're seeking an innovative AI Research Lead to pioneer next-generation artificial intelligence systems that will redefine industries. This role offers unparalleled opportunity to shape the future of human-machine collaboration in a cutting-edge environment.

Our ideal candidate thrives in ambiguity, combines deep technical expertise with visionary thinking, and is passionate about solving humanity's most complex challenges through ethical AI development. You'll lead a multidisciplinary team of researchers, publish groundbreaking papers, and translate theoretical breakthroughs into real-world applications.

Responsibilities

  • Architect and execute cutting-edge AI research roadmap for 2026 deployment
  • Lead a team of 8-10 researchers in developing novel neural network architectures
  • Collaborate with product teams to translate research into scalable commercial solutions
  • Secure $2M+ in annual research funding through grant proposals and industry partnerships
  • Publish 4+ peer-reviewed papers in top-tier AI conferences annually
  • Develop ethical AI frameworks aligned with emerging 2026 regulatory standards
  • Mentor junior researchers and foster cross-functional innovation

Qualifications

  • PhD in Computer Science, AI, or related field with 8+ years industry experience
  • Proven track record of publishing in NeurIPS/ICML/ICLR with 20+ citations
  • Expertise in transformer architectures, quantum computing integration, and federated learning
  • Experience leading research teams with $1M+ budgets
  • Strong Python/C++ proficiency with PyTorch/TensorFlow mastery
  • Deep understanding of 2026's emerging AI ethics and regulatory landscape
  • Exceptional communication skills for technical and non-technical stakeholders

Required Skills

AI Research Machine Learning Neural Networks Quantum Computing Ethics Team Leadership PyTorch TensorFlow Federated Learning Research Grants

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