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Senior AI Architect (2026 Vision)

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

Job Description

We are seeking a visionary Senior AI Architect to join our elite team at Nexus Horizon Systems. As we race toward the technological singularity anticipated for 2026, you will be at the forefront of designing the next generation of Artificial General Intelligence (AGI).

In this role, you will bridge the gap between theoretical research and scalable production engineering. You won't just be maintaining systems; you will be architecting the fundamental logic that powers our global neural network infrastructure. If you are obsessed with pushing the boundaries of what is possible in Machine Learning and Deep Learning, this is your opportunity to leave a lasting legacy.

Why join us?

  • Work on state-of-the-art Generative AI models.
  • Competitive compensation and equity packages.
  • Flexible remote-first culture with a high-tech office in SF.
  • Access to cutting-edge hardware and research datasets.

Responsibilities

  • Design and implement scalable, high-performance AI models capable of processing petabytes of data.
  • Lead the architectural direction for our next-gen Natural Language Processing (NLP) and Computer Vision modules.
  • Collaborate with cross-functional teams to integrate AI solutions into consumer products.
  • Optimize existing model inference pipelines to reduce latency and increase throughput by 40%.
  • Mentor junior engineers and researchers, fostering a culture of innovation and continuous learning.
  • Ensure all AI systems adhere to strict ethical guidelines and bias mitigation protocols.

Qualifications

  • PhD or Master’s degree in Computer Science, Mathematics, or a related field, with a focus on AI/ML.
  • 8+ years of professional experience in Machine Learning, Deep Learning, or AI Engineering.
  • Proven expertise in PyTorch, TensorFlow, or JAX.
  • Strong background in Large Language Models (LLMs) and Reinforcement Learning from Human Feedback (RLHF).
  • Experience with distributed computing systems (Kubernetes, Spark, Ray).
  • Exceptional problem-solving skills and ability to navigate ambiguity in fast-paced environments.

Required Skills

AI Machine Learning Deep Learning Python PyTorch TensorFlow NLP LLM Kubernetes Distributed Systems AGI Algorithm Design

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