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Quantum AI Researcher

Nexus 2026
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

Join Nexus 2026 at the forefront of technological revolution as we pioneer the next generation of quantum-AI hybrid systems. Our multidisciplinary team is developing breakthrough applications in cryptography, materials science, and autonomous decision-making. This role offers unparalleled opportunity to shape the technological landscape of the 2020s while working alongside Nobel laureates and Turing Award recipients in our state-of-the-art research facility.

We offer competitive equity packages, unlimited PTO, and comprehensive wellness programs including subsidized mindfulness retreats and biometric monitoring. Our campus features on-site childcare, gourmet dining, and dedicated innovation labs.

Responsibilities

  • Design and implement quantum algorithms optimized for classical-quantum hybrid architectures
  • Lead cross-functional R&D initiatives in quantum machine learning applications
  • Develop novel error-correction techniques for fault-tolerant quantum computing
  • Collaborate with hardware teams to translate theoretical models into practical implementations
  • Publish peer-reviewed research and present findings at international conferences
  • Mentor junior researchers and secure external funding through NSF/NIH grants
  • Contribute to open-source quantum computing frameworks

Qualifications

  • PhD in Physics, Computer Science, or Mathematics with quantum computing focus
  • 3+ years of hands-on experience with quantum programming languages (Q#, Qiskit, Cirq)
  • Publication record in top-tier journals (Nature, Science, etc.)
  • Expertise in quantum error correction and fault-tolerant architectures
  • Strong background in machine learning and neural networks
  • Proficiency in high-performance computing environments
  • Experience with cloud quantum computing platforms (IBM Quantum, Amazon Braket)

Required Skills

Quantum Computing Machine Learning Qiskit Cirq Q# Fault-Tolerant Computing Quantum Algorithms High-Performance Computing Python TensorFlow PyTorch Research Publication

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