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Quantum AI Research Engineer

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

Job Description

Join Nexus Quantum Labs at the frontier of computational intelligence as we pioneer the next generation of AI systems. We're seeking a visionary Quantum AI Research Engineer to architect hybrid quantum-classical models that will redefine machine learning by 2026. Collaborate with Nobel laureates and industry disruptors in our state-of-the-art research facility overlooking the Bay. This role offers unparalleled opportunities to shape the future of artificial intelligence while working with cutting-edge quantum hardware and proprietary neural networks.

Why Nexus Quantum Labs? We offer competitive compensation, unlimited PTO, comprehensive health benefits, and a $20,000 annual innovation stipend. Our culture values intellectual curiosity and rapid prototyping in a collaborative environment.

Responsibilities

  • Design and implement quantum neural network architectures for next-gen AI systems
  • Develop hybrid quantum-classical algorithms for optimization and simulation challenges
  • Lead experimental validation of quantum machine learning models on D-Wave and IBM systems
  • Collaborate with hardware teams to co-design quantum processors optimized for AI workloads
  • Publish breakthrough research in top-tier journals and conferences (Nature, NeurIPS, etc.)
  • Mentor junior researchers and drive cross-functional innovation sprints

Qualifications

  • PhD in Quantum Computing, Machine Learning, or Physics (MS with 5+ years experience considered)
  • Expertise in quantum circuit design and quantum algorithm development
  • Proficiency in Python, TensorFlow/PyTorch, and quantum SDKs (Qiskit, Cirq)
  • Published research in quantum machine learning or related fields
  • Experience with high-performance computing and distributed systems
  • Strong background in linear algebra, probability, and information theory
  • Demonstrated ability to translate theoretical concepts into practical implementations

Required Skills

Quantum Computing Machine Learning Python TensorFlow PyTorch Qiskit Cirq High-Performance Computing Neural Networks Algorithm Design

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