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Lead AI Architect | The 2026 Initiative

Apex Horizon Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Welcome to Apex Horizon Technologies, where we are engineering the future. We are currently seeking a visionary Lead AI Architect to spearhead The 2026 Initiative—our flagship project aimed at revolutionizing autonomous decision-making systems through next-generation neural networks.

In this role, you will define the technical roadmap for our proprietary AI framework, ensuring it scales efficiently across global markets. We are looking for a self-starter who thrives in ambiguity and possesses an unwavering commitment to excellence. If you are ready to build the infrastructure that powers tomorrow's economy, this is your stage.

Responsibilities

  • Architect and optimize end-to-end AI solutions for the 2026 Initiative, focusing on high-throughput data processing.
  • Lead a high-performance team of data scientists and ML engineers, fostering a culture of innovation and technical mentorship.
  • Design and implement proprietary machine learning models using PyTorch and TensorFlow.
  • Collaborate with cross-functional product teams to translate complex business requirements into robust technical architectures.
  • Ensure system scalability, security, and fault tolerance in distributed computing environments.
  • Conduct in-depth research into emerging AI trends, including Large Language Models (LLMs) and reinforcement learning.
  • Oversee the MLOps pipeline, ensuring seamless deployment and monitoring of production models.

Qualifications

  • Bachelor’s degree in Computer Science, Mathematics, or a related technical field (Master’s or PhD preferred).
  • 7+ years of experience in software engineering with a specific focus on Machine Learning and Artificial Intelligence.
  • Deep proficiency in Python, SQL, and distributed systems.
  • Extensive experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
  • Proven track record of deploying large-scale machine learning models to production environments.
  • Strong understanding of statistical modeling and algorithm optimization techniques.
  • Excellent communication skills with the ability to present complex technical concepts to non-technical stakeholders.

Required Skills

Python TensorFlow PyTorch AWS Kubernetes MLOps Machine Learning Deep Learning System Architecture

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