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AI Research Scientist - Future Tech Innovations

Quantum Leap Labs
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
Live Update
15 Mei 2026
Deadline
15 Mei 2027

Job Description

Join Quantum Leap Labs at the forefront of technological evolution. We're pioneering breakthroughs in quantum computing and AI integration that will define the 2026 digital landscape. As an AI Research Scientist, you'll architect next-generation neural networks and collaborate with Nobel laureates to solve humanity's most complex challenges. Our state-of-the-art facility offers unparalleled resources for experimentation, including access to quantum processors and a 10,000-core AI cluster.

We offer comprehensive benefits including equity, flexible hybrid work, and a $15,000 annual innovation budget. Shape the future with us.

Responsibilities

  • Design and implement novel deep learning architectures for quantum-classical hybrid systems
  • Lead research initiatives in explainable AI and ethical algorithm development
  • Collaborate with quantum computing teams to optimize AI-quantum workflows
  • Publish 2-3 peer-reviewed papers annually in top-tier AI/quantum journals
  • Mentor junior researchers and contribute to patent development
  • Develop predictive models for climate and healthcare applications using 2026-era data
  • Present findings at international conferences including NeurIPS and IEEE Quantum Week

Qualifications

  • PhD in Computer Science, Physics, or related field with 3+ years post-grad research
  • Expertise in TensorFlow/PyTorch and quantum programming frameworks (Qiskit, Cirq)
  • Published record in top-tier AI/quantum journals (NeurIPS, Nature Quantum)
  • Proficiency in high-performance computing environments (CUDA, MPI)
  • Demonstrated experience with large-scale distributed training
  • Strong background in theoretical physics or computational neuroscience
  • Ability to translate complex concepts into executable research roadmaps

Required Skills

Quantum Computing Deep Learning TensorFlow PyTorch Qiskit CUDA Distributed Training Explainable AI Research Methodology

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