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Senior AI Systems Architect (2026 Vision)

Apex Future Tech
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

We are seeking a visionary Senior AI Systems Architect to spearhead our research and engineering initiatives for the 2026 technology roadmap. At Apex Future Tech, we are building the infrastructure that will define the next decade of intelligent systems. You will be responsible for designing scalable, fault-tolerant machine learning platforms that power our cutting-edge products.

Why Join Us?

  • Work with the brightest minds in Artificial Intelligence and Quantum Computing.
  • Shape the architecture of systems that will be used by millions globally.
  • Competitive compensation package with equity options.

We are looking for a leader who is not just keeping up with the industry trends, but defining them.

Responsibilities

  • Architectural Leadership: Design and implement high-performance distributed ML systems and infrastructure capable of handling petabyte-scale data.
  • Strategic Roadmapping: Define the technical vision and 2026 roadmap for our core AI platforms, focusing on Agentic AI and Neural Symbolic integration.
  • Model Optimization: Lead efforts in model pruning, quantization, and hardware acceleration (CUDA, TensorRT) to maximize inference speed and efficiency.
  • Team Mentorship: Mentor junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
  • Collaboration: Partner with product managers and researchers to translate complex business requirements into robust technical solutions.

Qualifications

  • Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field; PhD is a plus.
  • Experience: 7+ years of professional experience in software engineering and machine learning systems architecture.
  • Technical Skills: Deep proficiency in Python, C++, and distributed computing frameworks (Kubernetes, Spark, Ray).
  • ML Expertise: Strong understanding of deep learning frameworks (PyTorch, TensorFlow, JAX) and experience with Large Language Models (LLMs).
  • Problem Solving: Proven track record of optimizing complex systems for performance, scalability, and cost-efficiency.

Required Skills

Python C++ PyTorch TensorFlow Kubernetes Spark Ray AWS GCP Distributed Systems Machine Learning Deep Learning LLMs CUDA TensorRT

Ready to Take This Challenge?

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