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Quantum AI Research Scientist

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

Job Description

Join Nexus Quantum Labs at the forefront of 2026's technological revolution as we pioneer the convergence of quantum computing and artificial intelligence. We seek a visionary Quantum AI Research Scientist to architect groundbreaking solutions that will redefine computational boundaries. In this pivotal role, you'll collaborate with Nobel laureates and industry disruptors to develop quantum neural networks, optimize machine learning algorithms, and solve previously unsolvable computational challenges. Our state-of-the-art facility in San Francisco offers unparalleled resources including 512-qubit quantum processors and exascale computing clusters. We offer competitive compensation, equity packages, and flexible work arrangements designed for the future of work.

Responsibilities

  • Design and implement novel quantum machine learning algorithms for next-gen AI systems
  • Lead cross-functional teams in developing quantum-optimized neural network architectures
  • Conduct cutting-edge research in quantum error correction and fault-tolerant computing
  • Translate theoretical quantum models into practical implementations using Python and C++
  • Collaborate with hardware engineers to co-design quantum-AI hybrid systems
  • Publish findings in top-tier journals and present at international conferences
  • Mentor junior researchers and drive innovation in quantum-AI methodologies

Qualifications

  • PhD in Quantum Computing, Computer Science, or Physics with 5+ years of research experience
  • Expertise in quantum algorithms, quantum machine learning, and tensor networks
  • Proficiency in quantum programming languages (Qiskit, Cirq) and classical ML frameworks
  • Publication record in quantum computing or AI research from top-tier venues
  • Deep understanding of quantum hardware constraints and optimization techniques
  • Experience with high-performance computing and parallel processing architectures
  • Strong background in linear algebra, probability theory, and computational complexity

Required Skills

Quantum Computing Machine Learning Python C++ Qiskit Cirq Neural Networks Quantum Algorithms Tensor Networks

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