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Information Technology 🏒 Full Time ⭐️ Verified

Lead AI Architect - 2026 Vision

Chronos 2026 Inc.
San Francisco
Estimated Salary
USD 180.000 – USD 240.000
Live Update
12 Mei 2026
Deadline
12 Mei 2027

Job Description

Are you ready to shape the technological landscape of the future? Chronos 2026 Inc. is at the forefront of pioneering autonomous systems and next-generation neural networks. We are seeking a visionary Lead AI Architect to spearhead our mission in defining the operational standards for 2026 and beyond.

In this pivotal role, you will bridge the gap between theoretical AI breakthroughs and scalable, real-world applications. You will lead a world-class team of engineers and data scientists, driving innovation that redefines human-machine interaction. If you are passionate about building the systems that will power the future, we want to hear from you.

Responsibilities

  • Architect and deploy scalable machine learning infrastructure for autonomous agents and quantum-enhanced systems.
  • Lead a cross-functional team of data scientists, ML engineers, and researchers to deliver high-impact AI solutions.
  • Define the strategic roadmap for AI evolution, ensuring alignment with the company's 2026 vision and long-term goals.
  • Optimize deep learning models for edge computing and high-throughput cloud environments.
  • Establish best practices for code quality, testing, and ethical AI governance.
  • Collaborate with product leadership to translate futuristic concepts into actionable technical roadmaps.
  • Mentor junior architects and engineers, fostering a culture of continuous learning and innovation.

Qualifications

  • PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
  • 10+ years of experience in software engineering, with at least 5 years in a lead architecture role within the AI/ML domain.
  • Expert proficiency in Python, PyTorch, TensorFlow, and modern GPU acceleration libraries.
  • Proven track record of designing and implementing large-scale distributed systems.
  • Deep understanding of machine learning lifecycles, including MLOps, model deployment, and A/B testing.
  • Strong experience with cloud platforms (AWS, Azure, or GCP) and containerization technologies (Docker/Kubernetes).
  • Familiarity with quantum computing principles and emerging tech paradigms is a significant advantage.

Required Skills

Python Machine Learning Deep Learning TensorFlow PyTorch Cloud Architecture MLOps Leadership AI Ethics

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