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Information Technology 🏒 Full Time ⭐️ Verified

Future-Ready AI Architect | San Francisco, CA

Nebula Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
17 Mei 2026
Deadline
17 Mei 2027

Job Description

Are you ready to architect the future of artificial intelligence for 2026 and beyond?

Nebula Innovations is seeking a visionary Senior AI Architect to lead the deployment of next-generation Large Language Models (LLMs) and generative AI systems. We are building the infrastructure that will define the digital landscape of the coming decade, and we need a technical expert to build scalable, resilient, and secure AI pipelines that handle enterprise-grade workloads.

You will bridge the gap between cutting-edge research and production-ready engineering, optimizing model performance, managing GPU clusters, and ensuring our AI systems are future-proof.

Responsibilities

  • Design and implement scalable MLOps pipelines for the deployment of LLMs and generative AI models.
  • Optimize inference latency and resource utilization across distributed GPU clusters and cloud environments.
  • Collaborate with data scientists to fine-tune models for specific domain applications and improve accuracy.
  • Implement robust security, privacy, and governance frameworks for AI model deployment and data handling.
  • Monitor system health, model drift, and performance using advanced observability tools.
  • Lead architectural reviews and mentor junior engineers on AI best practices and modern engineering stacks.
  • Stay ahead of the curve on emerging AI trends (e.g., AGI, Quantum AI integration) to guide our strategic roadmap.

Qualifications

  • Master’s degree in Computer Science, Artificial Intelligence, or a related field (or equivalent extensive experience).
  • 5+ years of experience in software engineering and machine learning infrastructure.
  • Deep proficiency in Python, PyTorch, TensorFlow, or JAX.
  • Experience with Kubernetes, Docker, and cloud platforms (AWS/GCP/Azure) for large-scale deployments.
  • Strong understanding of distributed systems, high-availability architecture, and caching strategies.
  • Experience with vector databases (e.g., Pinecone, Milvus) and RAG (Retrieval-Augmented Generation) architectures.
  • Demonstrated ability to work in a fast-paced, innovative environment.

Required Skills

Python PyTorch TensorFlow MLOps Kubernetes AWS AI Architecture Large Language Models Distributed Systems Machine Learning

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