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Quantum Machine Learning Engineer

Nexus Quantum Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
Live Update
13 Mei 2026
Deadline
13 Mei 2027

Job Description

Join Nexus Quantum Labs at the forefront of computational revolution! We're pioneering quantum machine learning solutions that will redefine 2026's technological landscape. As a Quantum Machine Learning Engineer, you'll architect hybrid quantum-classical systems that solve previously unsolvable problems in cryptography, materials science, and AI optimization. Our Austin innovation hub offers cutting-edge resources and collaborative freedom to transform theoretical breakthroughs into real-world applications.

Work alongside Nobel-caliber researchers in an environment that values audacious thinking and rigorous execution. We provide competitive equity, flexible schedules, and dedicated R&D time to explore your boldest ideas. This isn't just a jobβ€”it's your chance to shape the future of human-machine intelligence.

Responsibilities

  • Design and implement quantum algorithms for machine learning acceleration using frameworks like Qiskit and PennyLane
  • Develop hybrid quantum-classical neural networks for high-dimensional optimization problems
  • Collaborate with quantum hardware teams to optimize algorithm performance on emerging quantum processors
  • Create robust error mitigation strategies for practical quantum machine learning applications
  • Lead research initiatives in quantum neural networks and quantum-enhanced AI models
  • Translate complex quantum concepts into actionable engineering specifications
  • Contribute to open-source quantum ML libraries and publish breakthrough research

Qualifications

  • PhD in Quantum Computing, Machine Learning, or Physics with 3+ years industry experience
  • Expertise in quantum algorithms (QAOA, VQE, QNN) and quantum circuit design
  • Proficiency in Python with quantum ML libraries (Qiskit, Cirq, PennyLane)
  • Strong background in deep learning frameworks (PyTorch, TensorFlow)
  • Experience with quantum hardware integration (IBM Q, Rigetti, IonQ)
  • Published research in quantum machine learning or quantum computing
  • Demonstrated ability to solve complex optimization problems with quantum approaches
  • Excellent communication skills for technical and non-technical stakeholders

Required Skills

Quantum Computing Machine Learning Python Qiskit PyTorch Quantum Algorithms Neural Networks Optimization Research Hardware Integration

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