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AI Research Scientist - Quantum Computing

Nexus Labs
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
New
Live Update
21 Mei 2026
Deadline
21 Mei 2027

Job Description

Join Nexus Labs at the forefront of technological revolution as we pioneer the next generation of AI-quantum hybrid systems. We're seeking visionary AI Research Scientists to architect breakthrough algorithms that will redefine computational capabilities by 2026. This role offers unparalleled opportunities to collaborate with Nobel laureates, publish in top-tier journals, and shape the future of artificial intelligence. Our state-of-the-art facility in San Francisco provides cutting-edge resources including quantum annealers, neuromorphic processors, and petabyte-scale datasets.

We offer a comprehensive benefits package including equity grants, unlimited PTO, and relocation assistance for exceptional candidates. Work in an environment where your ideas become reality and your impact spans generations.

Responsibilities

  • Design and implement novel quantum machine learning algorithms for complex optimization problems
  • Lead cross-functional teams in developing AI systems capable of autonomous scientific discovery
  • Develop hybrid quantum-classical neural architectures for next-gen computational efficiency
  • Author peer-reviewed publications and patents in AI and quantum computing domains
  • Collaborate with hardware engineers to co-design quantum-resistant AI frameworks
  • Mentor junior researchers and establish new research methodologies in AI-quantum integration

Qualifications

  • PhD in Computer Science, Quantum Physics, or related field with 3+ years of industry research experience
  • Published work in top-tier AI/quantum computing conferences (NeurIPS, QIP, etc.)
  • Expertise in quantum machine learning frameworks (e.g., PennyLane, Qiskit) and high-performance computing
  • Proficiency in Python, TensorFlow/PyTorch, and quantum programming languages
  • Demonstrated ability to translate theoretical research into practical applications
  • Strong background in linear algebra, probability theory, and quantum information theory

Required Skills

Quantum Computing Machine Learning AI Research Python TensorFlow PyTorch Qiskit PennyLane High-Performance Computing Neural Networks Optimization Algorithms

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