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Quantum AI Research Scientist

Nexus Quantum Solutions
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
13 Mei 2026
Deadline
13 Mei 2027

Job Description

Join Nexus Quantum Solutions at the forefront of 2026's technological revolution as we pioneer quantum-AI convergence. We seek a visionary Quantum AI Research Scientist to develop groundbreaking algorithms that redefine computational boundaries. Work with cutting-edge quantum hardware and machine learning frameworks to solve previously impossible problems in cryptography, optimization, and molecular modeling. Our state-of-the-art lab offers unparalleled resources for experimentation, while our collaborative culture fosters innovation across interdisciplinary teams.

Why Nexus Quantum Solutions?

  • Access to next-gen quantum processors and proprietary AI platforms
  • Competitive equity package and comprehensive benefits
  • Opportunity to publish in top-tier journals and speak at global conferences
  • Flexible hybrid work model with quarterly innovation retreats

Responsibilities

  • Design and implement novel quantum machine learning algorithms for real-world applications
  • Collaborate with hardware engineers to optimize quantum circuit performance
  • Lead research initiatives in quantum neural networks and hybrid quantum-classical systems
  • Develop scalable solutions for quantum-enhanced AI in finance, healthcare, and logistics
  • Mentor junior researchers and publish findings in peer-reviewed publications
  • Secure intellectual property through patent applications
  • Present research findings to industry stakeholders and academic partners

Qualifications

  • PhD in Quantum Computing, Computer Science, or Physics with 3+ years of industry experience
  • Expertise in quantum programming languages (Qiskit, Cirq, or PennyLane)
  • Strong background in machine learning frameworks (PyTorch, TensorFlow) and algorithm optimization
  • Proven track record of publishing in quantum/AI conferences (QIP, NeurIPS)
  • Experience with quantum hardware integration and error mitigation techniques
  • Proficiency in Python, C++, and high-performance computing environments
  • Demonstrated ability to lead complex research projects from conception to deployment

Required Skills

Quantum Computing Machine Learning Algorithm Development Python C++ Qiskit Cirq TensorFlow PyTorch Quantum Hardware Cryptography Optimization

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