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Senior AI Architect: 2026 Protocol - San Francisco, CA

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

We are on the precipice of a new era in artificial intelligence, and Nexus Future Labs is leading the charge. We are seeking a visionary Senior AI Architect to design the core architecture of the 2026 Protocol, our proprietary cognitive infrastructure designed to surpass current neural network limitations. You will be responsible for building scalable, efficient, and secure systems that power our next-generation applications.

Why Join Us?

  • Work at the intersection of Quantum Computing and Generative AI.
  • Competitive equity package and remote-first flexibility.
  • Access to cutting-edge hardware and proprietary datasets.

If you are a technical leader who thrives in ambiguity and wants to define the standard for 2026 and beyond, we want to hear from you.

Responsibilities

  • Architectural Design: Lead the end-to-end design of the 2026 Protocol, ensuring scalability, fault tolerance, and high performance.
  • Model Optimization: Develop and implement advanced optimization techniques to reduce inference latency and resource consumption.
  • Research Integration: Bridge the gap between theoretical research and production-grade engineering.
  • Team Leadership: Mentor a team of machine learning engineers and data scientists.
  • Security & Ethics: Implement rigorous security protocols and ethical AI guidelines to prevent bias and ensure safety.
  • System Integration: Integrate AI models with legacy systems and cloud infrastructure (AWS/GCP).

Qualifications

  • Education: Master’s or PhD in Computer Science, Mathematics, or a related field (or equivalent experience).
  • Experience: 5+ years of experience in AI/ML engineering, with at least 2 years in a lead or architect role.
  • Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks.
  • Domain Knowledge: Deep understanding of Large Language Models (LLMs), Transformers, and Reinforcement Learning.
  • Infrastructure: Experience with cloud-native architecture and containerization (Docker, Kubernetes).
  • Problem Solving: Proven track record of solving complex technical challenges in high-pressure environments.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning Distributed Systems Cloud Architecture AWS Kubernetes

Ready to Take This Challenge?

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