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Quantum AI Research Lead

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

Job Description

Join Nexus Labs at the forefront of technological evolution as we pioneer the next wave of quantum-AI integration. We're seeking visionary Quantum AI Research Leads to architect breakthrough solutions that will redefine industries by 2026. Our dynamic environment combines cutting-edge quantum computing infrastructure with advanced machine learning frameworks, offering unparalleled opportunities to shape the future of computational intelligence.

As a key member of our Future Technologies Division, you'll collaborate with Nobel laureates and industry disruptors to develop scalable quantum algorithms, optimize neural networks for quantum environments, and lead cross-functional teams in deploying prototype systems. This role offers competitive equity, flexible work arrangements, and dedicated R&D resources to transform theoretical concepts into market-ready innovations.

Responsibilities

  • Design and implement novel quantum-AI hybrid algorithms for real-world applications
  • Lead cross-functional teams in developing quantum machine learning frameworks
  • Conduct independent research on quantum error correction and neural network optimization
  • Collaborate with hardware teams to co-design quantum processors compatible with AI workloads
  • Publish findings in peer-reviewed journals and present at international conferences
  • Mentor junior researchers and establish best practices for quantum-AI integration
  • Secure external funding through government grants and industry partnerships

Qualifications

  • PhD in Quantum Computing, Computer Science, or related field with 5+ years industry experience
  • Proven expertise in quantum algorithm design and quantum machine learning
  • Strong publication record in top-tier journals (e.g., Nature Quantum, IEEE Quantum)
  • Proficiency with quantum programming frameworks (Qiskit, Cirq, Q#) and AI toolkits
  • Experience leading technical teams and managing complex R&D projects
  • Demonstrated ability to translate theoretical research into practical applications
  • Deep understanding of quantum hardware limitations and error mitigation strategies

Required Skills

Quantum Computing Machine Learning Algorithm Design Research Leadership Quantum Machine Learning Qiskit Cirq Python TensorFlow PyTorch Project Management

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