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Artificial Intelligence 🏢 Full Time ⭐️ Verified

Lead AI Architect: Project 2026 - San Francisco, CA

Nexus Systems
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
11 Mei 2026
Deadline
11 Mei 2027

Job Description

We are looking for a visionary engineer to lead our Project 2026 initiative. Nexus Systems is at the forefront of the artificial intelligence revolution, and we are building the infrastructure for the future of autonomous reasoning. In this role, you will not just implement existing models; you will architect the next generation of generative systems, pushing the boundaries of what is possible in Large Language Models (LLMs) and multi-modal agents.

Why Nexus Systems?
We offer competitive equity, remote-first flexibility, and a culture that prioritizes innovation over bureaucracy. You will have access to the latest hardware accelerators and a team of the brightest minds in the tech industry.

Responsibilities

  • Define the Architecture: Lead the architectural design for proprietary AI models, focusing on scalability, efficiency, and safety in a production environment.
  • Model Optimization: Implement advanced quantization, pruning, and inference optimization techniques to reduce latency and cost for edge and cloud deployment.
  • Research & Development: Stay ahead of the curve by researching emerging trends in Neural Architecture Search (NAS) and Transformer variations.
  • Team Leadership: Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
  • Collaboration: Work closely with product teams to translate complex technical requirements into scalable AI solutions.

Qualifications

  • Education: PhD or Master's degree in Computer Science, Mathematics, or a related technical field.
  • Experience: 8+ years of experience in software engineering and 5+ years specifically in Deep Learning and Machine Learning.
  • Technical Skills: Proficiency in Python, PyTorch, and TensorFlow; experience with distributed training systems (e.g., Ray, Kubernetes).
  • Domain Knowledge: Strong understanding of NLP, Computer Vision, or Reinforcement Learning.
  • Problem Solving: Demonstrated ability to tackle complex, ambiguous problems with creative technical solutions.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning LLMs Distributed Systems Kubernetes CUDA Natural Language Processing Computer Vision

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