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Senior AI Architect (2026 Vision)

Nexus Horizon Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

Are you ready to build the intelligence of tomorrow? At Nexus Horizon Technologies, we are not just looking for an engineer; we are looking for a pioneer. As we race toward the future of technology, the integration of Generative AI and Autonomous Systems will redefine the digital landscape. We need a visionary Senior AI Architect to lead our cutting-edge research division and build the foundational models for 2026.


Why Join Us?

β€’ Work on next-gen Large Language Models (LLMs) and multimodal systems.
β€’ Competitive compensation package with equity options.
β€’ Flexible remote and hybrid work culture in the heart of Silicon Valley.
β€’ Access to state-of-the-art compute infrastructure and research grants.


We are looking for someone who thrives in ambiguity and is passionate about pushing the boundaries of what is possible in Artificial General Intelligence (AGI).

Responsibilities

  • Architect and deploy scalable Large Language Model (LLM) infrastructure and fine-tuning pipelines.
  • Pioneer research in reinforcement learning, generative adversarial networks, and autonomous agents.
  • Optimize neural network inference for edge devices and high-volume cloud environments.
  • Collaborate with product and engineering teams to integrate advanced AI capabilities into consumer-facing platforms.
  • Mentor junior engineers and establish best practices for MLOps and model governance.
  • Stay ahead of the curve in emerging AI trends, including semantic search and vector databases.

Qualifications

  • PhD or Master’s degree in Computer Science, Mathematics, Statistics, or a related quantitative field.
  • 5+ years of professional experience in Machine Learning or Artificial Intelligence engineering.
  • Deep expertise in PyTorch, TensorFlow, and modern deep learning frameworks.
  • Proven track record of working with Vector Databases (Pinecone, Milvus) and Retrieval-Augmented Generation (RAG) architectures.
  • Strong proficiency in distributed systems, cloud architecture (AWS/GCP), and containerization (Docker/Kubernetes).
  • Excellent communication skills with the ability to translate complex technical concepts for non-technical stakeholders.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP LLMs AWS Kubernetes Docker MLOps Stanford MIT PhD AI Research

Ready to Take This Challenge?

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