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Senior AI Architect 2026

Nexus Future Systems
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
1 Juli 2026
Deadline
1 Jul 2027

Job Description

Are you ready to build the intelligence layer of tomorrow? Nexus Future Systems is seeking a visionary Senior AI Architect to spearhead our R&D division focused on the year 2026 and beyond. We are not just predicting the future; we are architecting it through next-generation artificial intelligence.

In this role, you will lead the development of proprietary Large Language Models (LLMs) and autonomous agent frameworks designed to solve complex global challenges. You will work at the intersection of deep learning, distributed systems, and ethical AI, ensuring our solutions are scalable, robust, and transformative.

Responsibilities

  • Architect and deploy scalable machine learning pipelines capable of processing exabytes of data.
  • Lead research initiatives in Generative AI, Reinforcement Learning, and Neural Architecture Search.
  • Optimize model inference latency to support real-time, high-frequency applications.
  • Establish MLOps best practices, including CI/CD for models, automated testing, and monitoring.
  • Collaborate with product teams to translate cutting-edge research into production-ready features.
  • Ensure AI systems adhere to strict ethical guidelines and bias mitigation protocols.

Qualifications

  • Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field.
  • Minimum of 5 years of experience in AI/ML engineering, with at least 2 years in a leadership or senior architect role.
  • Expert proficiency in Python, PyTorch, TensorFlow, and modern deep learning frameworks.
  • Strong understanding of distributed computing (Kubernetes, Docker) and cloud infrastructure (AWS/GCP).
  • Experience with fine-tuning LLMs and implementing Retrieval-Augmented Generation (RAG).
  • Proven track record of delivering complex AI projects from conception to deployment.

Required Skills

Python Machine Learning Deep Learning NLP PyTorch TensorFlow Kubernetes AWS MLOps Generative AI Neural Networks Big Data

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