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Quantum AI Research Lead

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

Job Description

Join Nexus Labs at the forefront of technological evolution as we pioneer the next generation of quantum-AI hybrid systems. We're seeking visionary research leaders to architect breakthrough solutions that will redefine computing by 2026. This role offers unparalleled access to cutting-edge quantum hardware, AI infrastructure, and a world-class research environment where your innovations can transform industries.

Our multidisciplinary team operates at the intersection of quantum physics, machine learning, and computational theory. You'll collaborate with Nobel laureates, AI pioneers, and quantum hardware engineers to develop scalable algorithms, optimize quantum neural networks, and solve previously intractable problems in cryptography, drug discovery, and climate modeling.

Responsibilities

  • Design and implement quantum-AI hybrid architectures for enterprise-scale applications
  • Lead research initiatives in quantum machine learning and neural network optimization
  • Develop proprietary algorithms leveraging quantum supremacy for real-world problem-solving
  • Collaborate with hardware teams to co-design quantum processors optimized for AI workloads
  • Publish peer-reviewed research and secure patents in emerging quantum-AI domains
  • Mentor cross-functional teams in quantum computing principles and AI integration
  • Drive strategic partnerships with academic institutions and quantum hardware providers

Qualifications

  • PhD in Quantum Computing, Machine Learning, or Computational Physics with 5+ years of research experience
  • Expertise in quantum programming languages (Q#, Qiskit, Cirq) and quantum circuit optimization
  • Proven track record of developing production-level AI systems with quantum-enhanced capabilities
  • Strong background in tensor networks, quantum error correction, and variational quantum algorithms
  • Experience with large-scale distributed computing frameworks (Spark, Kubernetes, HPC)
  • Demonstrated ability to translate theoretical research into practical industry applications
  • Prior publications in top-tier journals (Nature, Science, IEEE) or quantum computing conferences

Required Skills

Quantum Computing Machine Learning AI Research Quantum Algorithms Q# Qiskit Python TensorFlow PyTorch HPC Distributed Systems

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