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Lead AI Architect (2026 Roadmap)

Zai Global
San Francisco
Estimated Salary
USD 200.000 – USD 280.000
New
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

Are you ready to shape the technological landscape of the next decade? Zai Global is seeking a visionary Lead AI Architect to spearhead our 2026 Strategic AI Initiative. We are not just building software; we are architecting the future of human-computer interaction through next-generation Generative AI and Neural Processing Units.

In this pivotal role, you will bridge the gap between theoretical research and production-grade engineering, ensuring our models are scalable, ethical, and ready for global deployment. If you thrive in a fast-paced, high-impact environment and want to define the standard for AI in 2026, we want to meet you.

Responsibilities

  • Architect Future-Proof Systems: Design and implement scalable machine learning pipelines capable of handling exabyte-scale data for the 2026 release cycle.
  • Model Optimization: Lead research into quantization and pruning techniques to enhance inference speed on edge devices.
  • Generative AI Leadership: Oversee the development of proprietary Large Language Models (LLMs) and multimodal AI agents.
  • MLOps Integration: Establish robust CI/CD pipelines for AI model training, validation, and deployment.
  • Ethical AI Compliance: Implement rigorous bias detection and fairness protocols to ensure responsible AI deployment.

Qualifications

  • Education: MS or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
  • Experience: 7+ years of experience in deep learning, with a focus on NLP or Computer Vision.
  • Technical Proficiency: Expert-level knowledge of Python, PyTorch, TensorFlow, and Hugging Face Transformers.
  • System Design: Proven track record of designing high-availability distributed systems.
  • Leadership: Demonstrated ability to mentor junior engineers and lead cross-functional teams.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP LLMs MLOps System Design Leadership

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