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Information Technology 🏢 Full Time ⭐️ Verified

AI Systems Architect - 2026 Tech Vision

QuantumLeap Innovations
Austin
Estimated Salary
USD 190.000 – USD 280.000
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Shape the future of artificial intelligence at QuantumLeap Innovations. We're seeking a visionary AI Systems Architect to design next-generation neural networks that will redefine industries by 2026. Join our elite team of pioneers developing autonomous AI ecosystems for climate modeling, quantum computing interfaces, and decentralized machine learning networks.

Our Austin headquarters features state-of-the-art neuro-symbolic computing labs, unlimited research budgets, and cross-functional collaboration with Nobel laureates. This hybrid role offers 4-day workweeks, equity grants, and exclusive access to our global AI incubator.

Responsibilities

  • Architect multi-agent reinforcement learning systems for 2026-scale industrial applications
  • Design quantum-resistant AI frameworks for national security infrastructure
  • Lead development of neural-symbolic hybrid computing platforms
  • Optimize AI models for edge deployment in autonomous systems
  • Collaborate with ethics committees to align AI development with 2026 regulatory standards
  • Pioneer carbon-neutral AI training methodologies
  • Mentor junior researchers in emerging AI paradigms

Qualifications

  • PhD in Computer Science/AI or equivalent with 8+ years in neural architecture design
  • Published research in top-tier AI conferences (NeurIPS, ICML, ICLR) post-2020
  • Expertise in quantum machine learning frameworks (Qiskit, Cirq)
  • Proven experience deploying AI systems at >100M parameter scale
  • Deep understanding of transformer architectures beyond standard implementations
  • Proficiency in federated learning and differential privacy
  • Strong background in AI ethics and alignment research

Required Skills

AI Architecture Quantum Computing Neural Networks Reinforcement Learning Ethics in AI Federated Learning Quantum Machine Learning

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