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Artificial Intelligence 🏒 Full Time ⭐️ Verified

Principal AI Architect | Shaping the Future of 2026

Nexus Horizon Labs
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

The Opportunity:

Nexus Horizon Labs is pioneering the next generation of Artificial General Intelligence (AGI). We are looking for a visionary Principal AI Architect to lead our core research division. In this pivotal role, you will architect the foundational models that will define the technological landscape of 2026 and beyond.

If you are passionate about pushing the boundaries of machine learning, optimizing transformer architectures, and building systems that think, we want to hear from you.

Why Join Us?

  • Impact: Work on projects that will shape the future of human-computer interaction.
  • Innovation: Access to cutting-edge hardware and a culture of radical experimentation.
  • Growth: Competitive equity package and continuous learning opportunities.

Key Responsibilities:

Responsibilities

  • Architect and implement scalable Large Language Model (LLM) pipelines with a focus on efficiency and hallucination reduction.
  • Lead the R&D strategy for proprietary model training, fine-tuning, and alignment techniques.
  • Collaborate with cross-functional teams to integrate AI models into production-grade consumer applications.
  • Optimize inference latency and throughput using techniques like quantization and distillation.
  • Mentor senior engineers and researchers, fostering a culture of technical excellence.
  • Stay ahead of industry trends to ensure our roadmap remains competitive in the rapidly evolving 2026 landscape.

Qualifications

  • PhD or Master’s degree in Computer Science, Mathematics, Physics, or a related technical field.
  • 7+ years of experience in machine learning, deep learning, or NLP.
  • Expert proficiency in Python, PyTorch, and modern ML frameworks.
  • Deep understanding of transformer architectures, attention mechanisms, and reinforcement learning from human feedback (RLHF).
  • Experience with MLOps tools (Docker, Kubernetes, MLflow) and cloud platforms (AWS, GCP, or Azure).
  • Strong problem-solving skills and the ability to translate theoretical research into practical solutions.

Required Skills

Python PyTorch TensorFlow Large Language Models (LLMs) NLP Deep Learning MLOps Cloud Computing AI Architecture Reinforcement Learning CUDA

Ready to Take This Challenge?

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