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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Architect - Project 2026

Nexus Future Systems
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
10 Juli 2026
Deadline
10 Jul 2027

Job Description

We are currently seeking a visionary Senior AI Architect to lead the technical strategy for our flagship initiative, Project 2026. This role is not just about coding; it is about architecting the neural infrastructure that will define the next decade of intelligent systems. If you are passionate about pushing the boundaries of Generative AI, Large Language Models (LLMs), and scalable cloud architectures, we want to hear from you.

As part of Nexus Future Systems, you will work with a world-class team of researchers and engineers dedicated to solving complex problems for enterprise clients. You will define the technical roadmap for our AI products, ensuring they are robust, scalable, and ahead of the curve.

Responsibilities

  • Architect and implement scalable AI and Machine Learning infrastructure for Project 2026, focusing on high-throughput and low-latency environments.
  • Lead the design of our proprietary LLMs, optimizing model performance for enterprise deployment using techniques like quantization and distillation.
  • Collaborate with product managers and engineering leads to translate business requirements into technical specifications.
  • Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.
  • Ensure the security, compliance, and ethical use of AI models within our systems.
  • Stay abreast of the latest advancements in the AI landscape and integrate relevant breakthroughs into our architecture.

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field; PhD is a plus.
  • Minimum of 7+ years of experience in software engineering, with a focus on Machine Learning or Artificial Intelligence.
  • Strong proficiency in Python and deep experience with PyTorch or TensorFlow.
  • Proven track record of deploying production-grade AI models at scale using cloud platforms like AWS or GCP.
  • Experience with MLOps tools, containerization (Docker/Kubernetes), and CI/CD pipelines.
  • Excellent problem-solving skills and the ability to thrive in a fast-paced, dynamic startup environment.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning AWS GCP Kubernetes MLOps AI Architecture

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