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Information Technology 🏢 Full Time ⭐️ Verified

AI Systems Architect

InnovateTech Solutions
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
17 Mei 2026
Deadline
17 Mei 2027

Job Description

Join InnovateTech Solutions at the forefront of technological evolution! As an AI Systems Architect, you'll design and implement cutting-edge AI infrastructure that powers the next generation of autonomous systems and intelligent applications. This role offers unparalleled opportunities to shape the future of human-machine collaboration while working alongside world-class engineers in our state-of-the-art San Francisco headquarters.

We're seeking visionary architects to build scalable AI frameworks that will revolutionize industries from healthcare to transportation. You'll lead the end-to-end lifecycle of AI system design, from conceptualization to deployment and optimization. If you're passionate about pushing boundaries and creating solutions that redefine what's possible, this is your moment.

Responsibilities

  • Design and implement scalable AI infrastructure supporting real-time processing of petabyte-scale datasets
  • Architect cloud-native AI systems leveraging AWS/Azure/GCP with 99.99% uptime SLAs
  • Develop MLOps pipelines enabling continuous model training and deployment at enterprise scale
  • Lead cross-functional teams to integrate AI solutions with legacy and emerging technologies
  • Optimize system performance through advanced neural network architectures and quantum computing hybrids
  • Define AI governance frameworks ensuring ethical, auditable, and bias-resistant systems
  • Drive innovation through prototype development of next-gen AI capabilities

Qualifications

  • 10+ years in AI/ML system architecture with 5+ years in distributed computing environments
  • Expertise in TensorFlow, PyTorch, and large language model optimization techniques
  • Proven experience designing fault-tolerant systems for mission-critical AI applications
  • Advanced knowledge of quantum machine learning algorithms and hybrid computing architectures
  • Strong background in blockchain-based AI verification and decentralized data ecosystems
  • Published research in top-tier AI conferences (NeurIPS, ICML, CVPR) or equivalent industry impact
  • Professional certifications in AWS/Azure/GCP ML and Google Quantum AI

Required Skills

AI Architecture Machine Learning Quantum Computing MLOps Cloud Platforms Neural Networks AI Ethics Distributed Systems

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