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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Scientist - 2026 Visionary

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

Job Description

Join Nexus Future Labs at the forefront of 2026's technological revolution. We're pioneering autonomous AI systems that will redefine human-machine collaboration. As an AI Research Scientist, you'll architect next-generation neural networks and quantum-entangled computing models to solve humanity's grandest challenges. Our multidisciplinary teams work in state-of-the-art labs with unlimited computational resources, publishing breakthrough research in Science and Nature. We offer equity grants, flexible hybrid work, and sabbatical programs for deep-dive research.

Responsibilities

  • Design and implement quantum-resistant AI algorithms for 2026-era cybersecurity infrastructure
  • Lead cross-functional teams in developing AGI (Artificial General Intelligence) frameworks
  • Author peer-reviewed publications on human-AI symbiosis and ethical AI alignment
  • Optimize neural networks for neuromorphic computing architectures
  • Collaborate with neuroscientists to develop brain-computer interface protocols
  • Drive open-source initiatives in explainable AI and federated learning
  • Present findings at global conferences like AI World 2026

Qualifications

  • PhD in Machine Learning, Quantum Computing, or Computational Neuroscience (or equivalent experience)
  • 3+ years publishing top-tier AI research at NeurIPS/ICML/ICLR
  • Expertise in transformer architectures, reinforcement learning, and quantum machine learning
  • Proficiency in PyTorch, TensorFlow, and quantum programming languages
  • Strong background in AI ethics and value alignment research
  • Experience with distributed computing frameworks (Ray, Kubernetes)
  • Track record of translating research into production AI systems

Required Skills

Quantum Computing AGI Research Neural Networks Machine Learning Quantum Machine Learning Reinforcement Learning PyTorch TensorFlow AI Ethics Distributed Computing

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