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Lead Generative AI Architect (2026 Vision)

Nebula Dynamics
San Francisco
Estimated Salary
USD 190.000 – USD 260.000
New
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

We are building the technological foundation for the year 2026 and beyond. At Nebula Dynamics, we are not just predicting the future; we are engineering it. We are seeking a visionary Lead Generative AI Architect to spearhead our next-generation multimodal AI initiatives. You will be responsible for designing the neural architectures that will power the next wave of autonomous agents and generative systems.


In this role, you will bridge the gap between theoretical research and production-grade deployment, ensuring our models are scalable, efficient, and ethically sound. Join us in shaping the intelligence of tomorrow.

Responsibilities

  • Architect and deploy state-of-the-art Large Language Models (LLMs) optimized for real-time inference.
  • Lead a high-performing team of ML engineers and data scientists to push the boundaries of Generative AI capabilities.
  • Design robust training pipelines handling petabyte-scale datasets for the 2026 roadmap.
  • Implement advanced fine-tuning and alignment techniques (RLHF, DPO) to enhance model safety and alignment.
  • Collaborate with product teams to integrate AI agents into complex enterprise workflows.
  • Establish best practices for MLOps, monitoring, and observability in high-stakes environments.

Qualifications

  • Master’s or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
  • 8+ years of professional experience in deep learning, NLP, or Generative AI.
  • Expert proficiency in Python, PyTorch, and distributed computing frameworks (Ray, Kubernetes).
  • Deep understanding of Transformer architectures, diffusion models, and attention mechanisms.
  • Proven track record of shipping production-level AI models with measurable impact.
  • Strong leadership skills with experience mentoring technical talent.

Required Skills

Python PyTorch TensorFlow Large Language Models NLP Machine Learning Deep Learning Distributed Systems MLOps Artificial Intelligence Transformer Architecture Generative Models

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