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Information Technology 🏢 Full Time ⭐️ Verified

Quantum AI Research Engineer

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
22 Mei 2026
Deadline
22 Mei 2027

Job Description

Join Nexus Future Labs at the forefront of technological evolution. We're pioneering the convergence of quantum computing and artificial intelligence to solve humanity's most complex challenges. As a Quantum AI Research Engineer, you'll architect next-gen algorithms that redefine computational boundaries. Our multidisciplinary team operates at the intersection of physics, machine learning, and distributed systems in a state-of-the-art lab environment. Benefit from industry-leading resources, flexible work arrangements, and direct impact on breakthrough innovations shaping 2026 and beyond.

Responsibilities

  • Design and implement quantum machine learning algorithms for real-world applications
  • Develop hybrid quantum-classical computing architectures for optimization problems
  • Collaborate with physicists to translate quantum phenomena into practical AI frameworks
  • Lead research initiatives in quantum neural networks and quantum-enhanced data analysis
  • Author peer-reviewed publications and patent novel quantum AI methodologies
  • Mentor junior researchers and contribute to open-source quantum AI ecosystems

Qualifications

  • PhD in Quantum Computing, Computer Science, or Physics (MS with exceptional experience)
  • Proficiency in quantum programming languages (Qiskit, Cirq, Q#)
  • Deep expertise in machine learning frameworks (PyTorch, TensorFlow) and algorithm optimization
  • Published research in quantum machine learning or quantum information theory
  • Experience with high-performance computing and distributed systems
  • Demonstrated ability to translate theoretical concepts into production-ready solutions
  • Strong background in linear algebra, probability, and computational complexity

Required Skills

Quantum Computing Machine Learning Python Qiskit Cirq PyTorch Distributed Systems Algorithm Optimization Quantum Information Theory

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