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Information Technology 🏒 Full Time ⭐️ Verified

Future-Ready AI Architect

Nebula Horizon Systems
San Francisco
Estimated Salary
USD 160.000 – USD 220.000
Live Update
19 Mei 2026
Deadline
19 Mei 2027

Job Description

Shape the Infrastructure of Tomorrow.

Nebula Horizon Systems is pioneering the next generation of intelligent software. As we accelerate toward our aggressive 2026 roadmap, we are seeking a visionary Future-Ready AI Architect to lead our platform evolution.

In this pivotal role, you will not just maintain systems; you will architect the very fabric of our AI-driven ecosystem. We value bold thinking, technical excellence, and a passion for solving complex problems at scale. If you are ready to define the standards for 2026 and beyond, we want to meet you.

Responsibilities

  • Lead the architectural design and implementation of scalable machine learning models and AI infrastructure.
  • Drive the roadmap for system modernization to ensure readiness for the 2026 technological landscape.
  • Collaborate with data science and engineering teams to integrate AI solutions seamlessly into production environments.
  • Establish best practices for MLOps, security, and data governance across the organization.
  • Optimize existing codebases and infrastructure for performance, energy efficiency, and cost-effectiveness.
  • Mentor junior engineers and contribute to a culture of continuous innovation.

Qualifications

  • Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
  • Minimum of 5+ years of experience in software engineering with a strong focus on AI/ML systems.
  • Expert proficiency in Python, TensorFlow, PyTorch, or similar deep learning frameworks.
  • Strong experience with cloud infrastructure (AWS, Azure, or GCP) and containerization (Docker/Kubernetes).
  • Demonstrated ability to design fault-tolerant, high-availability systems.
  • Experience with MLOps pipelines, data pipelines, and real-time processing technologies.

Required Skills

Python TensorFlow PyTorch AWS Azure Kubernetes MLOps System Design Machine Learning Deep Learning

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