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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI & Quantum Systems Architect

Nexus Horizon Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

Join the Architects of Tomorrow.
Nexus Horizon Labs is pioneering the infrastructure for the post-classical computing era. We are seeking a visionary Senior AI & Quantum Systems Architect to lead our roadmap for 2026 and beyond. In this role, you will bridge the gap between classical computing and quantum supremacy, deploying next-generation neural networks that redefine industry standards.

As a key member of our Core Infrastructure team, you will design resilient, scalable architectures capable of handling the computational demands of tomorrow’s AI applications.

Responsibilities

  • Architectural Leadership: Design and oversee the implementation of hybrid quantum-AI systems and high-performance computing infrastructure.
  • Roadmap Strategy: Define technical roadmaps that align with our 2026 vision for technological singularity and AI integration.
  • System Optimization: Drive the optimization of deep learning models and quantum circuits to ensure maximum efficiency and throughput.
  • Cross-Functional Collaboration: Work closely with R&D, Data Science, and Security teams to integrate emerging technologies into our production environment.
  • Security & Compliance: Implement robust security protocols and compliance measures for sensitive data processing in quantum environments.
  • Mentorship: Mentor junior engineers and foster a culture of innovation, technical excellence, and continuous learning.

Qualifications

  • Education: PhD or Master’s degree in Computer Science, Physics, Mathematics, or a related field (or equivalent extensive experience).
  • Technical Expertise: 10+ years of experience in Systems Architecture, with a strong focus on AI/ML and high-performance computing.
  • Quantum Experience: Hands-on experience with quantum computing frameworks (e.g., Qiskit, Cirq, PennyLane) and classical deep learning frameworks (PyTorch, TensorFlow).
  • Cloud Mastery: Advanced proficiency in cloud platforms (AWS, Azure, or GCP) with a focus on GPU/TPU clusters.
  • Distributed Systems: Deep understanding of distributed systems, microservices, and containerization (Docker, Kubernetes).
  • Communication: Exceptional ability to translate complex technical concepts into clear strategic narratives for stakeholders.

Required Skills

Quantum Computing Machine Learning Deep Learning Python C++ AWS Azure Kubernetes System Architecture Cloud Infrastructure

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