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Senior AI Architect (2026 Vision)

Nexus Future Tech
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
19 Mei 2026
Deadline
19 Mei 2027

Job Description

Shape the Future of Intelligence

Nexus Future Tech is a leading pioneer in next-generation artificial intelligence. We are building the foundational models that will define the technological landscape of 2026 and beyond. We are looking for a visionary Senior AI Architect to lead our research and deployment strategies.

If you are passionate about pushing the boundaries of Large Language Models (LLMs), Generative AI, and autonomous systems, we want to hear from you. Join a diverse team of engineers, ethicists, and strategists dedicated to solving humanity's most complex challenges.

Why Nexus Future Tech?

  • Impactful Work: Your code will power the next generation of smart applications.
  • Top-Tier Compensation: Competitive salary and equity packages.
  • Remote-First Culture: Flexible work arrangements with a global team.
  • Cutting-Edge Tech: Access to the latest hardware and cloud infrastructure.

Responsibilities

  • Architect and design scalable, high-performance AI/ML systems for 2026 readiness.
  • Lead the research and development of Generative AI models, including LLMs and diffusion models.
  • Collaborate with cross-functional teams to integrate AI solutions into production environments.
  • Define technical strategies for data pipelines, model training, and MLOps infrastructure.
  • Mentor junior engineers and researchers, fostering a culture of innovation and excellence.
  • Evaluate emerging AI technologies to determine their applicability to Nexus Future Tech's roadmap.

Qualifications

  • PhD or Master's degree in Computer Science, Mathematics, or a related field.
  • 10+ years of experience in software engineering, with at least 5 years in AI/ML architecture.
  • Deep expertise in deep learning frameworks (PyTorch, TensorFlow, JAX).
  • Strong proficiency in Python and distributed systems.
  • Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
  • Proven track record of deploying production-grade machine learning models at scale.

Required Skills

Python PyTorch TensorFlow MLOps AWS Kubernetes NLP Computer Vision Deep Learning Distributed Systems

Ready to Take This Challenge?

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