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Senior AI Architect (2026 Horizon)

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

Job Description

We are seeking a visionary Senior AI Architect to lead our cutting-edge projects targeting the technological landscape of 2026. At Nexus Future Systems, we are not just building software; we are architecting the future. You will be at the forefront of designing scalable, efficient, and groundbreaking AI systems that will define the next generation of human-computer interaction. If you are passionate about the convergence of deep learning, generative AI, and futuristic infrastructure, we want to hear from you.

Responsibilities

  • Design and implement scalable AI/ML architectures focused on 2026 readiness and long-term scalability.
  • Lead the research and development of proprietary large language models and generative algorithms.
  • Oversee the end-to-end machine learning lifecycle, from data ingestion and model training to deployment and monitoring.
  • Collaborate with cross-functional teams of engineers, data scientists, and product managers to translate complex business requirements into technical solutions.
  • Establish best practices for code quality, MLOps pipelines, and CI/CD to ensure robust system performance.
  • Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
  • Stay ahead of industry trends in AI, quantum computing, and edge processing to drive continuous improvement.

Qualifications

  • Master’s or PhD in Computer Science, Mathematics, or a related field (or equivalent practical experience).
  • Minimum of 7+ years of experience in software engineering, with at least 4 years specifically in AI/ML architecture.
  • Deep expertise in Python, PyTorch, TensorFlow, or JAX.
  • Proven track record of designing and deploying production-grade machine learning models at scale.
  • Strong understanding of NLP, Computer Vision, or Reinforcement Learning.
  • Familiarity with cloud infrastructure (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
  • Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

Python PyTorch TensorFlow MLOps Machine Learning Architecture NLP Cloud Computing Docker Kubernetes Generative AI

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