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Artificial Intelligence 🏢 Full Time ⭐️ Verified

Senior AI Architect (2026 Vision)

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

Job Description

Are you ready to define the trajectory of Artificial Intelligence for the next decade? Nexus Future Labs is seeking a visionary Senior AI Architect to spearhead our 2026 strategic roadmap.

In this pivotal role, you will not just write code; you will architect the neural foundations of tomorrow's most impactful applications. We are looking for a leader who understands the current state of Large Language Models (LLMs) and possesses the foresight to engineer the next leap in AGI capabilities.

We are building the infrastructure for the 2026 era of computing—where AI is seamless, omnipresent, and deeply integrated into the fabric of digital reality. If you are driven by complexity and inspired by the future, we want to meet you.

Responsibilities

  • Design and implement scalable, distributed AI infrastructure specifically optimized for 2026 scalability demands.
  • Lead the architecture of proprietary large-scale transformer models and multi-modal AI systems.
  • Optimize model inference latency and drastically reduce compute costs through advanced quantization and pruning techniques.
  • Collaborate with cross-functional teams to integrate ethical AI principles and safety guardrails into core development lifecycles.
  • Establish technical standards for data governance, model versioning, and reproducible research.
  • Drive innovation in Reinforcement Learning from Human Feedback (RLHF) for next-gen chat interfaces.

Qualifications

  • Ph.D. or Master’s degree in Computer Science, Mathematics, or a related technical field.
  • 5+ years of professional experience in Machine Learning Engineering or Applied AI.
  • Expert proficiency in Python, PyTorch, and TensorFlow.
  • Deep understanding of Deep Learning architectures, NLP, and Computer Vision.
  • Proven track record of deploying high-performance ML models into production environments.
  • Experience with cloud-native AI platforms (AWS SageMaker, GCP AI Platform, or Azure ML).

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP Distributed Systems Cloud Computing AWS GCP

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