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Lead AI Architect (Quantum-Integrated Systems) - San Francisco, CA

Nexus Core Systems
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
8 Juli 2026
Deadline
8 Jul 2027

Job Description

Join the Future of Intelligence.

We are seeking a visionary Lead AI Architect to spearhead the development of Quantum-Integrated Neural Networks for 2026 and beyond. At Nexus Core Systems, we are building the infrastructure that will power the next generation of autonomous decision-making. If you possess a deep understanding of machine learning, quantum mechanics, and high-performance computing, we want to talk to you.

In this role, you will bridge the gap between theoretical AI research and practical silicon implementation, ensuring our systems remain at the cutting edge of technological evolution.

Responsibilities

  • Architect Neural Architectures: Design and implement scalable deep learning models optimized for hybrid quantum-classical computing environments.
  • Quantum Integration: Lead the research and integration of quantum algorithms into existing neural network workflows to enhance processing capabilities.
  • Technical Leadership: Mentor a team of senior data scientists and engineers, fostering a culture of innovation and technical excellence.
  • System Optimization: Oversee the deployment of AI models on high-performance computing clusters (HPC) to ensure low-latency inference.
  • Roadmap Planning: Define the technical roadmap for our AI infrastructure, anticipating 2026 trends in AI safety and efficiency.
  • Collaboration: Work closely with hardware engineers to optimize algorithms for specific quantum processor architectures.

Qualifications

  • Education: Master’s or Ph.D. in Computer Science, Physics, Applied Mathematics, or a related field.
  • Experience: 8+ years of experience in machine learning engineering, with at least 3 years in a lead or architect role.
  • Technical Stack: Proficiency in Python, C++, TensorFlow, PyTorch, and experience with quantum computing frameworks (e.g., Cirq, Qiskit).
  • Knowledge: Deep understanding of quantum mechanics principles as applied to computing and quantum error correction.
  • Soft Skills: Exceptional communication skills, with the ability to translate complex technical concepts to diverse stakeholders.
  • Problem Solving: Demonstrated ability to solve complex, multi-dimensional problems in high-pressure environments.

Required Skills

Python C++ TensorFlow PyTorch Quantum Computing HPC Machine Learning Deep Learning Neural Networks Leadership

Ready to Take This Challenge?

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