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Quantum AI Research Engineer 2026

Nexus Quantum Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

Join Nexus Quantum Labs at the forefront of 2026's technological revolution. 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 neural networks operating in quantum superposition, pushing beyond classical computational boundaries. Our Austin hub offers state-of-the-art quantum hardware and collaborative labs where your innovations will directly shape the future of autonomous systems, drug discovery, and climate modeling.

We seek visionaries who thrive at the intersection of theoretical physics and machine learning. You'll collaborate with Nobel laureates and publish breakthrough research in Nature Quantum while developing commercial applications that will redefine industries. This isn't just research—it's engineering the fabric of 2026's digital reality.

Responsibilities

  • Design and implement quantum neural networks using Qiskit and TensorFlow Quantum frameworks
  • Develop hybrid quantum-classical algorithms for optimization problems unsolvable by classical systems
  • Lead experimental validation of quantum AI models on 50+ qubit processors
  • Create patent-pending methodologies for error correction in quantum machine learning pipelines
  • Collaborate with biotech teams to accelerate protein folding simulations using quantum annealing
  • Author white papers and open-source libraries advancing quantum AI accessibility
  • Mentor junior researchers in quantum machine learning best practices

Qualifications

  • PhD in Quantum Computing, Physics, or Computer Science (or equivalent industry experience)
  • Proficiency in Python, Qiskit, and quantum circuit design principles
  • Published research in quantum machine learning or quantum algorithms
  • Experience with quantum hardware providers (IBM Quantum, Rigetti, IonQ)
  • Deep understanding of quantum entanglement and superposition phenomena
  • Strong background in linear algebra, probability theory, and statistical modeling
  • Track record of translating theoretical concepts into practical implementations

Required Skills

Quantum Computing Machine Learning Qiskit TensorFlow Quantum Python Quantum Algorithms Neural Networks Physics AI Research Austin Tech

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