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Quantum AI Research Engineer

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
New
Live Update
1 Juni 2026
Deadline
1 Jun 2027

Job Description

Join Nexus Future Labs at the forefront of technological evolution as a Quantum AI Research Engineer. We're pioneering the convergence of quantum computing and artificial intelligence to solve humanity's most complex challenges. In this role, you'll architect next-generation quantum neural networks, develop hybrid quantum-classical algorithms, and collaborate with Nobel laureates to redefine computational boundaries. Our state-of-the-art facility in downtown San Francisco offers unparalleled resources including 128-qubit processors and exascale simulation clusters.

As part of our elite Future Systems Division, you'll contribute to breakthroughs in drug discovery, climate modeling, and materials science while mentoring the next generation of quantum pioneers. We offer competitive equity packages, unlimited learning stipends, and flexible remote work options for exceptional candidates. If you're driven to transform theoretical possibilities into tangible solutions that will shape 2026 and beyond, this is your calling.

Responsibilities

  • Design and implement quantum neural network architectures for accelerated machine learning
  • Develop error-corrected quantum algorithms for high-dimensional optimization problems
  • Create hybrid quantum-classical frameworks for real-world industrial applications
  • Lead cross-functional teams in prototyping quantum-AI solutions for healthcare and logistics
  • Publish breakthrough research in Nature Quantum and IEEE Quantum journals
  • Secure $5M+ in quantum computing grants from NSF and DARPA
  • Mentor PhD researchers in quantum machine learning methodologies

Qualifications

  • PhD in Quantum Computing, AI, or Computational Physics with 3+ years industry experience
  • Expertise in quantum programming languages (Q#, Qiskit, Cirq) and circuit optimization
  • Proven track record of developing production-grade quantum algorithms
  • Strong background in machine learning frameworks (PyTorch, TensorFlow) and GPU acceleration
  • Published research in quantum machine learning or quantum error correction
  • Experience with quantum hardware providers (IBM Quantum, Rigetti, IonQ)
  • Ability to translate complex quantum concepts into business applications

Required Skills

Quantum Computing Machine Learning AI Q# Qiskit Cirq PyTorch TensorFlow Quantum Error Correction Neural Networks GPU Acceleration Research

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