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Information Technology 🏢 Full Time ⭐️ Verified

AI Infrastructure Architect

Nexus Quantum Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
11 Mei 2026
Deadline
11 Mei 2027

Job Description

Join Nexus Quantum Labs at the forefront of AI infrastructure innovation. We're seeking a visionary AI Infrastructure Architect to design quantum-resistant systems for 2026 and beyond. This role bridges bleeding-edge research with scalable production environments, ensuring our AI models operate at unprecedented efficiency and security. You'll lead the transformation of legacy systems into next-generation quantum-safe architectures while mentoring a team of engineers in our state-of-the-art San Francisco facility.

Responsibilities

  • Design quantum-resistant AI infrastructure supporting 10,000+ GPU clusters
  • Architect hybrid cloud/on-prem solutions for real-time AI inference at edge locations
  • Implement zero-trust security frameworks for distributed AI training pipelines
  • Optimize energy consumption in data centers using advanced cooling technologies
  • Develop automation frameworks for ML model deployment at global scale
  • Lead cross-functional teams in adopting next-gen hardware accelerators
  • Define technical roadmaps for AI infrastructure evolution through 2028

Qualifications

  • 10+ years in distributed systems architecture with 5+ in AI/ML infrastructure
  • Expertise in Kubernetes, TensorFlow, and PyTorch deployment ecosystems
  • Certification in quantum computing security protocols (e.g., NIST Post-Quantum standards)
  • Proven track record of scaling AI systems to petabyte-scale data processing
  • Deep understanding of GPU/TPU optimization and interconnect technologies
  • Experience with carbon-neutral data center design and operations
  • Published research in AI infrastructure or quantum-resistant cryptography

Required Skills

AI Infrastructure Quantum Computing Kubernetes TensorFlow Zero-Trust Security GPU Optimization Distributed Systems Cloud Architecture Edge Computing ML Deployment NIST Standards Carbon-Neutral Design

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