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Lead AI Architect - Generative Systems

Apex Future Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
24 Mei 2026
Deadline
24 Mei 2027

Job Description

We are seeking a visionary Lead AI Architect to spearhead our next-generation generative intelligence systems. As we prepare for the technological landscape of 2026, you will be responsible for designing scalable, secure, and ethical AI infrastructures that power our core products. You will work at the intersection of machine learning, software engineering, and product strategy to deliver transformative solutions.

Why Join Us?
We offer a competitive salary, equity package, and the opportunity to work on projects that define the future of human-computer interaction. Our team is composed of industry pioneers dedicated to pushing the boundaries of what is possible in artificial intelligence.

Responsibilities

  • Architect and deploy large-scale generative AI models (LLMs) using PyTorch and TensorFlow.
  • Lead the end-to-end machine learning lifecycle, from data ingestion and preprocessing to model fine-tuning and productionization.
  • Collaborate with cross-functional teams of data scientists, engineers, and product managers to define technical requirements and roadmaps.
  • Implement robust MLOps pipelines to ensure model monitoring, versioning, and continuous integration/deployment.
  • Ensure AI systems adhere to strict ethical guidelines, data privacy regulations, and bias mitigation strategies.
  • Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.

Qualifications

  • 5+ years of experience in software engineering with a focus on machine learning and artificial intelligence.
  • Deep expertise in Python, C++, and modern ML frameworks (PyTorch, TensorFlow, Hugging Face).
  • Proven track record of designing and deploying production-grade AI systems at scale.
  • Experience with vector databases, RAG (Retrieval-Augmented Generation), and fine-tuning LLMs.
  • M.S. or Ph.D. in Computer Science, Machine Learning, or a related technical field.
  • Strong understanding of cloud architectures (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning LLM Natural Language Processing MLOps Docker Kubernetes AWS GCP

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