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Information Technology 🏒 Full Time ⭐️ Verified

AI Architect 2026 - San Francisco, CA

Nebula Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
25 Mei 2026
Deadline
25 Mei 2027

Job Description

We are on the frontier of the AI revolution, building the intelligent systems of tomorrow. We are seeking a visionary AI Architect 2026 to join our elite technical team in San Francisco. In this pivotal role, you will design and deploy next-generation machine learning models that solve complex, real-world problems at scale.

You will be at the helm of our AI infrastructure, ensuring our systems are not only cutting-edge but also ethical, scalable, and resilient. If you are passionate about the future of technology and possess a deep understanding of neural networks and large language models, we want to hear from you.

Join us in shaping the trajectory of artificial intelligence for the years ahead.

Responsibilities

  • Architect and implement end-to-end machine learning pipelines for large-scale data processing and model training.
  • Lead the research and development of novel AI algorithms and models tailored for 2026 technological standards.
  • Collaborate with cross-functional teams of data scientists, engineers, and product managers to integrate AI solutions into our core products.
  • Optimize existing models for speed, accuracy, and resource efficiency, utilizing techniques such as quantization and pruning.
  • Ensure compliance with AI ethics guidelines and data privacy regulations in all development processes.
  • Mentor junior engineers and establish best practices for AI engineering within the organization.

Qualifications

  • PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
  • Proven experience (5+ years) in designing, training, and deploying production-grade machine learning models.
  • Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
  • Deep understanding of Deep Learning architectures, NLP, and Computer Vision.
  • Experience with MLOps tools (Docker, Kubernetes, MLflow) and cloud platforms (AWS, GCP, or Azure).
  • Strong problem-solving skills and the ability to thrive in a fast-paced, high-growth environment.

Required Skills

Python Machine Learning Deep Learning NLP PyTorch TensorFlow MLOps AWS GCP Docker Kubernetes Data Science

Ready to Take This Challenge?

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