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Information Technology 🏢 Full Time ⭐️ Verified

Quantum Machine Learning Researcher

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

Job Description

Join Nexus Quantum Dynamics at the forefront of 2026's technological revolution. We're pioneering quantum machine learning solutions to solve humanity's most complex challenges. As a Quantum ML Researcher, you'll architect next-gen algorithms that leverage quantum supremacy to transform industries. Our state-of-the-art lab in San Francisco offers unparalleled resources to push the boundaries of computational intelligence.

This role requires deep expertise in both quantum physics and advanced ML frameworks. You'll collaborate with Nobel laureates and industry disruptors to develop hybrid quantum-classical systems that outperform traditional computing paradigms. We offer competitive compensation, unlimited research funding, and flexible work arrangements for optimal innovation.

Responsibilities

  • Design and implement quantum neural networks for complex pattern recognition
  • Develop hybrid quantum-classical algorithms for optimization problems
  • Conduct experimental validation of quantum ML models on real quantum hardware
  • Lead cross-functional teams to integrate quantum solutions into enterprise systems
  • Author breakthrough research publications in top-tier journals and conferences
  • Secure funding through competitive grant applications and industry partnerships
  • Mentor junior researchers and contribute to open-source quantum ML frameworks

Qualifications

  • PhD in Quantum Computing, Machine Learning, or related field
  • 3+ years of experience with quantum programming languages (Q#, Qiskit, Cirq)
  • Expertise in deep learning frameworks (PyTorch, TensorFlow) with quantum extensions
  • Published research in quantum machine learning or quantum information theory
  • Proficiency in high-performance computing environments and cloud quantum services
  • Strong mathematical background in linear algebra, probability, and quantum mechanics
  • Experience with quantum hardware platforms (IBM Quantum, Rigetti, IonQ)
  • Track record of translating theoretical models into practical implementations

Required Skills

Quantum Computing Machine Learning Qiskit Cirq PyTorch TensorFlow Quantum Algorithms High-Performance Computing Python C++ Research

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