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2026 Quantum AI Researcher

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

Job Description

Join Nexus Labs at the forefront of technological evolution as we pioneer solutions for 2026 and beyond. We're seeking visionary Quantum AI Researchers to develop next-generation algorithms that will redefine computational boundaries. In this role, you'll collaborate with Nobel laureates and industry disruptors to create scalable quantum machine learning models for climate modeling, drug discovery, and autonomous systems.

Why Nexus Labs? Our state-of-the-art facility features a 1000-qubit quantum processor and offers unlimited compute resources. We provide competitive equity packages, flexible work arrangements, and dedicated innovation time for personal projects.

Responsibilities

  • Design and implement quantum neural networks for complex optimization problems
  • Develop hybrid quantum-classical ML frameworks for real-world applications
  • Lead research initiatives in quantum-resistant cryptography and AI safety
  • Collaborate with hardware teams to co-design quantum processors
  • Publish breakthrough research in top-tier journals and conferences
  • Mentor junior researchers and lead cross-functional project teams
  • Secure funding through NSF and DARPA grant applications

Qualifications

  • PhD in Quantum Computing, Machine Learning, or related field
  • 3+ years of hands-on experience with quantum programming languages (Qiskit, Cirq)
  • Published research in quantum machine learning or quantum algorithms
  • Expertise in Python/C++ with deep learning frameworks (PyTorch, TensorFlow)
  • Strong background in linear algebra, probability, and quantum mechanics
  • Experience with cloud quantum computing platforms (IBM Quantum, Amazon Braket)
  • Proven ability to translate theoretical concepts into practical implementations

Required Skills

Quantum Computing Machine Learning AI Research Python C++ Qiskit PyTorch Quantum Algorithms Cryptography

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