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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Scientist (Quantum Computing)

Nexus Innovations
San Francisco
Estimated Salary
USD 190.000 – USD 280.000
Live Update
17 Mei 2026
Deadline
17 Mei 2027

Job Description

Join Nexus Innovations at the forefront of 2026's technological revolution as an AI Research Scientist specializing in Quantum Computing. We're pioneering the next generation of AI systems that transcend classical limitations, and we need visionary minds to help us unlock unprecedented computational power. This role offers the rare opportunity to shape the future of human-machine collaboration while working with world-class researchers in our state-of-the-art San Francisco lab.

As a key member of our Quantum AI division, you'll develop hybrid quantum-classical algorithms that solve previously intractable problems in drug discovery, climate modeling, and autonomous systems. We provide competitive compensation, flexible work arrangements, and a culture that celebrates intellectual curiosity and bold experimentation.

Responsibilities

  • Design and implement quantum machine learning algorithms leveraging Q# and TensorFlow Quantum frameworks
  • Develop novel error-correction techniques for quantum neural networks
  • Collaborate with quantum hardware engineers to optimize AI models for quantum processors
  • Lead cross-functional projects integrating quantum AI solutions into commercial applications
  • Publish breakthrough research in top-tier journals and present at international conferences
  • Mentor junior researchers and contribute to patent development
  • Stay ahead of emerging quantum AI standards and regulatory frameworks

Qualifications

  • PhD in Quantum Computing, Machine Learning, or related field (or equivalent experience)
  • Expertise in quantum algorithms and quantum circuit design
  • Proficiency in Python, Q#, and quantum computing libraries (Cirq, PennyLane)
  • Proven track record of publishing in quantum AI or machine learning
  • Experience with hybrid quantum-classical frameworks
  • Strong background in linear algebra, probability theory, and information theory
  • Demonstrated ability to translate complex research into practical applications

Required Skills

Quantum Computing Machine Learning Q# Python TensorFlow Quantum Cirq PennyLane Quantum Algorithms Error Correction Neural Networks

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