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Information Technology 🏒 Full Time ⭐️ Verified

Next-Gen AI Architect 2026 | San Francisco, CA

Nexus Horizon Solutions
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
11 Mei 2026
Deadline
11 Mei 2027

Job Description

We are on the precipice of a new era in artificial intelligence. At Nexus Horizon Solutions, we are not just building applications for today; we are architecting the intelligent systems of tomorrow. We are seeking a visionary Next-Gen AI Architect to lead our R&D division in defining the technology landscape for 2026.

In this pivotal role, you will be at the forefront of Generative AI, Large Language Models, and autonomous agent development. You will define the technical roadmap that bridges the gap between theoretical research and scalable production environments, pushing the boundaries of what is possible in AI.

Responsibilities

  • Architect and deploy state-of-the-art AI models and machine learning pipelines optimized for 2026 standards.
  • Lead research initiatives focused on Generative AI, Natural Language Processing, and Computer Vision.
  • Collaborate with cross-functional teams to integrate advanced AI capabilities into core products.
  • Ensure ethical AI practices, data privacy, and fairness in model training and deployment.
  • Mentor junior engineers and establish best practices for the high-performance AI engineering team.
  • Optimize model inference speed and reduce latency for real-time, immersive applications.

Qualifications

  • Master’s or Ph.D. in Computer Science, AI, or a related quantitative field.
  • 5+ years of experience in machine learning engineering or AI research.
  • Expert proficiency in Python, PyTorch, and TensorFlow.
  • Deep understanding of LLMs, fine-tuning techniques, and RAG architectures.
  • Strong background in distributed systems and cloud infrastructure (AWS/GCP).
  • Exceptional problem-solving skills and a passion for innovation in the future tech space.

Required Skills

Python PyTorch TensorFlow Large Language Models Machine Learning Engineering AWS Generative AI Deep Learning

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