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Quantum AI Research Engineer

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

Job Description

Shape the future of human-machine intelligence at Nexus Future Labs. We're pioneering the intersection of quantum computing and artificial intelligence to solve humanity's most complex challenges. As a Quantum AI Research Engineer, you'll develop cutting-edge algorithms that leverage quantum mechanics to accelerate machine learning breakthroughs. Our state-of-the-art lab in San Francisco offers unparalleled resources to transform theoretical possibilities into tangible innovations.

Join a multidisciplinary team of Nobel laureates, quantum physicists, and AI visionaries. You'll work on projects ranging from quantum neural networks to encrypted AI models, with direct access to quantum hardware partnerships. This role offers unparalleled opportunities to publish groundbreaking research and influence the trajectory of 2026's technological landscape.

Responsibilities

  • Design and implement quantum-enhanced machine learning algorithms for NLP and computer vision
  • Develop hybrid quantum-classical computing frameworks for real-world applications
  • Optimize quantum circuits to accelerate AI training processes
  • Collaborate with hardware teams to bridge quantum hardware limitations with software solutions
  • Lead research initiatives in quantum cryptography for secure AI systems
  • Publish findings in top-tier journals and present at international quantum conferences
  • Mentor junior researchers and contribute to open-source quantum AI projects

Qualifications

  • PhD in Quantum Computing, Machine Learning, or Physics with 3+ years industry experience
  • Expertise in quantum programming languages (Qiskit, Cirq, Q#) and classical AI frameworks
  • Published research in quantum machine learning or quantum information theory
  • Strong background in linear algebra, quantum mechanics, and computational complexity
  • Proficiency in Python, TensorFlow/PyTorch, and high-performance computing
  • Demonstrated ability to translate theoretical concepts into practical implementations
  • Experience with quantum hardware platforms (IBM Quantum, Rigetti, IonQ)

Required Skills

Quantum Computing Machine Learning AI Research Qiskit Cirq Quantum Algorithms Python TensorFlow Cryptography High-Performance Computing

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