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Quantum AI Architect

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

Shape the quantum frontier at Nexus Future Labs. We're pioneering AI-quantum hybrid systems that will redefine computational capabilities by 2026. Join our elite team of visionaries to architect next-generation algorithms that solve previously impossible challenges in cryptography, materials science, and climate modeling. This is your chance to work at the intersection of quantum mechanics and artificial intelligence, with resources unmatched in the industry.

Our state-of-the-art quantum lab features 1000+ qubit processors and dedicated GPU clusters. You'll collaborate with Nobel laureates and industry disruptors while contributing to patents that will shape the next decade of technology. We offer competitive equity packages, flexible work arrangements, and continuous learning opportunities through our Future Skills Academy.

Responsibilities

  • Design and implement quantum machine learning algorithms for practical 2026-era applications
  • Develop hybrid quantum-classical neural architectures for exponential speedup
  • Lead cross-functional teams of quantum physicists, AI researchers, and software engineers
  • Optimize quantum circuit designs for error correction and scalability
  • Translate complex quantum concepts into viable business solutions for Fortune 500 partners
  • Author white papers and patents advancing the state of quantum AI
  • Contribute to our open-source quantum AI framework used by 200+ research institutions

Qualifications

  • PhD in Quantum Computing, Machine Learning, or Physics with 3+ years industry experience
  • Expertise in quantum programming languages (Q#, Qiskit, Cirq) and quantum circuit optimization
  • Proven track record of publishing in top-tier quantum/AI conferences (e.g., QIP, NeurIPS)
  • Deep understanding of quantum error correction protocols and fault-tolerant computing
  • Experience with large-scale distributed computing frameworks (Spark, Dask)
  • Strong background in linear algebra, probability theory, and information theory
  • Portfolio demonstrating 2+ quantum AI projects with measurable performance gains

Required Skills

Quantum Computing Machine Learning Q# Qiskit Cirq Neural Networks Cryptography Distributed Computing Python C++ TensorFlow PyTorch

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