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Information Technology 🏢 Full Time ⭐️ Verified

AI Systems Architect 2026

QuantumLeap Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
23 Mei 2026
Deadline
23 Mei 2027

Job Description

Join QuantumLeap Dynamics at the forefront of technological evolution as we architect the AI systems that will define 2026. We seek visionary engineers to design next-generation neural networks, quantum-AI hybrids, and autonomous decision frameworks that will revolutionize industries. Our team operates in a cutting-edge lab environment where innovation isn't just encouraged—it's mandated. If you're passionate about solving problems that don't yet have solutions, this is your calling.

Responsibilities

  • Design and implement scalable AI architectures integrating quantum computing principles
  • Lead R&D initiatives for explainable AI frameworks and ethical alignment systems
  • Develop autonomous decision protocols for real-time adaptive systems
  • Collaborate with cross-functional teams to deploy AI solutions in production environments
  • Pioneer breakthroughs in neuromorphic computing and synthetic consciousness research
  • Drive innovation in edge AI optimization for IoT ecosystems
  • Author technical whitepapers and patents for AI paradigm-shifting technologies

Qualifications

  • PhD in Computer Science, AI, or Quantum Physics with 5+ years industry experience
  • Expertise in transformer architectures, reinforcement learning, and quantum algorithms
  • Proven track record of deploying production-grade AI systems at scale
  • Mastery of Python, TensorFlow, PyTorch, and quantum programming languages
  • Deep understanding of ethical AI frameworks and bias mitigation strategies
  • Published research in top-tier AI/quantum computing conferences (NeurIPS, ICML, QIP)
  • Experience with distributed computing frameworks (Kubernetes, Spark) and cloud-native development

Required Skills

AI Architecture Quantum Computing Machine Learning Neural Networks Python TensorFlow PyTorch Quantum Algorithms Reinforcement Learning Distributed Systems Ethics in AI

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