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Information Technology 🏒 Full Time ⭐️ Verified

Senior AI Architect

2026
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
24 Mei 2026
Deadline
24 Mei 2027

Job Description

We are 2026, a forward-thinking technology company dedicated to defining the future of intelligent systems. We are seeking a highly skilled Senior AI Architect to lead the architectural design and implementation of our next-generation machine learning infrastructure. If you are passionate about building scalable, resilient systems and want to shape the technological landscape of tomorrow, we want to meet you.

In this pivotal role, you will be responsible for designing end-to-end AI solutions that drive our core products forward.

Responsibilities

  • Architect and design scalable machine learning pipelines and deep learning models for high-volume data processing.
  • Lead the technical strategy for integrating AI models into production environments using cloud-native technologies.
  • Collaborate with data scientists and software engineers to optimize model performance and reduce latency.
  • Establish best practices for MLOps, CI/CD, and code quality across the engineering team.
  • Conduct rigorous code reviews and technical architecture planning sessions.
  • Stay abreast of cutting-edge research in AI and evaluate emerging technologies for potential integration.

Qualifications

  • PhD or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
  • 8+ years of experience in software engineering or machine learning architecture.
  • Expert proficiency in Python, C++, and modern deep learning frameworks (TensorFlow, PyTorch).
  • Strong understanding of distributed systems, microservices architecture, and cloud platforms (AWS, GCP, or Azure).
  • Experience with containerization technologies (Docker, Kubernetes) and orchestration.
  • Proven track record of leading technical teams and mentoring junior engineers.

Required Skills

Python TensorFlow PyTorch AWS Kubernetes Docker MLOps Machine Learning Deep Learning Distributed Systems

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