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AI Research Scientist (2026 Vision)

Nexus Labs
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
New
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Join Nexus Labs at the forefront of technological evolution as we pioneer solutions for 2026 and beyond. We seek visionary AI Research Scientists to shape the next generation of intelligent systems that will redefine industries. Our cutting-edge environment combines deep research with real-world application, offering unparalleled opportunities to work on quantum-entangled neural networks, generative AI frameworks, and autonomous decisioning systems. Collaborate with Nobel laureates and Turing Award winners in our state-of-the-art facility overlooking the Bay. We provide competitive equity packages, unlimited research budgets, and flexible work arrangements designed for peak innovation.

Responsibilities

  • Design and implement novel AI architectures for 2026-era applications
  • Lead breakthrough research in quantum machine learning and generative AI
  • Develop ethical AI frameworks aligned with future regulatory landscapes
  • Publish findings in top-tier journals and present at global conferences
  • Mentor junior researchers and cross-functional innovation teams
  • Secure patents for proprietary AI methodologies and systems
  • Collaborate with industry partners to translate research into commercial solutions

Qualifications

  • PhD in Computer Science, AI, or related field with 5+ years research experience
  • Proven track record of publishing in NeurIPS/ICML/ICLR or equivalent
  • Expertise in transformer architectures, reinforcement learning, and distributed computing
  • Proficiency in PyTorch/TensorFlow and C++ for high-performance systems
  • Strong background in ethics, bias mitigation, and responsible AI development
  • Experience securing $1M+ in research funding or industry partnerships
  • Portfolio demonstrating deployment of research into production systems

Required Skills

AI Research Machine Learning Quantum Computing Neural Networks Generative AI PyTorch TensorFlow Reinforcement Learning Ethics in AI

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