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Information Technology 🏢 Full Time ⭐️ Verified

AI Systems Architect

Nexus Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
15 Mei 2026
Deadline
15 Mei 2027

Job Description

Join Nexus Innovations at the forefront of technological evolution for 2026. We're seeking a visionary AI Systems Architect to design and implement next-generation artificial intelligence frameworks that will redefine industries. This role offers unparalleled opportunity to shape the future of autonomous systems, predictive analytics, and human-AI collaboration in our state-of-the-art San Francisco innovation hub.

You'll lead cross-functional teams in developing scalable AI architectures while ensuring ethical alignment with emerging global tech standards. Our culture rewards bold innovation and provides unlimited resources to transform ambitious concepts into reality.

Responsibilities

  • Design and implement scalable AI/ML infrastructure supporting real-time decision-making at petabyte scale
  • Lead development of quantum-resistant neural networks for 2026-era security requirements
  • Architect human-AI symbiosis interfaces enabling seamless workforce augmentation
  • Optimize AI systems for edge-to-cloud deployment across hybrid quantum-classical environments
  • Establish ethical governance frameworks for autonomous system behavior
  • Drive innovation in federated learning architectures for cross-organizational data collaboration
  • Lead technical strategy for AI integration with emerging IoT ecosystems

Qualifications

  • 10+ years in AI/ML system architecture with 5+ years in leadership roles
  • Expertise in transformer architectures, federated learning, and quantum computing interfaces
  • Proven track record deploying production-grade AI systems processing 10M+ daily transactions
  • Deep knowledge of ethical AI frameworks (EU AI Act, NIST RMF)
  • Proficiency in cloud-native AI deployment (AWS SageMaker, GCP Vertex AI, Azure ML)
  • Experience with neuromorphic computing and brain-computer interface systems
  • PhD or equivalent in Computer Science, AI, or related quantitative field
  • Published research in top-tier AI/ML conferences (NeurIPS, ICML, CVPR)

Required Skills

Artificial Intelligence Machine Learning System Architecture Quantum Computing Neural Networks Cloud Computing Ethics in AI Data Science

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