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Quantum AI Research Lead

Nexus Systems Inc.
Austin
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

Join Nexus Systems at the forefront of technological evolution as we pioneer the next wave of AI-Quantum convergence. We're seeking a visionary Quantum AI Research Lead to architect breakthrough solutions that will redefine industries by 2026. You'll lead a multidisciplinary team in developing hybrid quantum-neural networks, pushing the boundaries of computational intelligence while solving real-world challenges in cryptography, drug discovery, and climate modeling.

Why Nexus? We offer unparalleled resources including access to IBM Quantum systems, NVIDIA's latest GPU clusters, and a $500M R&D budget. Our Austin campus features state-of-the-art labs, flexible workspaces, and a culture that rewards bold innovation.

Responsibilities

  • Design and implement quantum machine learning algorithms for 2026-era applications
  • Lead cross-functional teams of quantum physicists, AI specialists, and domain experts
  • Develop error-corrected quantum neural networks with fault-tolerant architectures
  • Secure patents for novel quantum-AI hybrid methodologies
  • Collaborate with NASA, Mayo Clinic, and Fortune 500 partners on applied research
  • Mentor PhD researchers and publish in Nature/Science journals
  • Shape the company's 2026 technology roadmap for quantum supremacy

Qualifications

  • PhD in Quantum Computing, Machine Learning, or Physics (with 5+ years postdoc)
  • Published research in quantum algorithms or quantum machine learning
  • Expertise in Qiskit, Cirq, or equivalent quantum SDKs
  • Proficiency in TensorFlow/PyTorch with quantum extensions
  • Experience leading teams in high-stakes R&D environments
  • Strong background in quantum error correction and fault tolerance
  • Track record of translating theory into commercial applications
  • Clearance for DoD/DoE projects preferred

Required Skills

Quantum Computing Machine Learning Qiskit TensorFlow Fault-Tolerant Systems Neural Networks Cryptography Algorithm Design Team Leadership

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