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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Scientist - 2026 Visionary

QuantumLeap Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
5 Juli 2026
Deadline
5 Jul 2027

Job Description

Join QuantumLeap Dynamics at the forefront of technological evolution as we pioneer the next wave of AI breakthroughs targeting 2026. We seek a visionary AI Research Scientist to architect transformative solutions that will redefine industries. You'll collaborate with Nobel laureates and industry disruptors in our state-of-the-art quantum computing lab, pushing the boundaries of neural networks and autonomous systems. This role offers unparalleled opportunities to shape humanity's digital future while enjoying unparalleled benefits including equity, flexible schedules, and dedicated R&D budgets.

Responsibilities

  • Lead cutting-edge research in quantum machine learning and neural architecture optimization
  • Develop scalable AI frameworks for autonomous systems and predictive analytics
  • Author breakthrough publications in top-tier journals and conferences
  • Mentor cross-functional teams in AI ethics and responsible implementation
  • Secure $2M+ in annual research grants and industry partnerships
  • Prototype and validate AI solutions targeting 2026 commercialization milestones
  • Present findings to C-suite executives and government innovation councils

Qualifications

  • PhD in Computer Science, AI, or Quantum Computing with 5+ years industry experience
  • Published 15+ peer-reviewed papers in top AI/ML venues (NeurIPS, ICML)
  • Expertise in transformer architectures, reinforcement learning, and federated learning
  • Proven track record of securing competitive research grants
  • Proficiency in Python, PyTorch, TensorFlow, and quantum computing frameworks
  • Experience with MLOps pipelines and large-scale distributed training
  • Demonstrated leadership in cross-disciplinary AI projects

Required Skills

AI Research Machine Learning Quantum Computing Neural Networks Deep Learning Reinforcement Learning PyTorch TensorFlow MLOps Research Grants

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