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Lead Quantum AI Architect (2026 Horizon)

Chronos Dynamics
San Francisco
Estimated Salary
USD 195.000 – USD 260.000
New
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

Chronos Dynamics is at the forefront of the technological revolution, pioneering the advancements required for the year 2026. We are seeking a visionary Lead Quantum AI Architect to lead our research division. In this role, you will bridge the gap between theoretical quantum physics and practical, scalable artificial intelligence applications. If you are passionate about building the future of computing and want to define the standards of the next decade, we want to hear from you.

Why Join Us?

  • Work on groundbreaking projects that define the future of the industry.
  • Competitive compensation package and equity options.
  • Access to state-of-the-art quantum computing resources.
  • Flexible work environment in the heart of San Francisco.

Responsibilities

  • Design and implement complex quantum algorithms tailored for machine learning tasks.
  • Oversee the integration of Quantum Processing Units (QPUs) with existing cloud infrastructure.
  • Lead a team of elite engineers and researchers in developing next-gen AI models.
  • Conduct feasibility analysis for "post-silicon" computing architectures.
  • Establish best practices for quantum error correction and noise mitigation.
  • Drive the technical roadmap for the 2026 product release cycle.
  • Collaborate with academic institutions to stay ahead of quantum breakthroughs.

Qualifications

  • PhD in Computer Science, Physics, or a related quantitative field.
  • Minimum of 8-10 years of experience in AI/ML and software development.
  • Strong background in quantum mechanics and quantum computing theory.
  • Proficiency in programming languages such as Python, C++, and Qiskit/Cirq.
  • Proven ability to lead cross-functional technical teams.
  • Experience with high-performance computing (HPC) environments.

Required Skills

Quantum Computing Artificial Intelligence Machine Learning Python C++ San Francisco CA Research

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