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AI Research Scientist (2026 Vision)

Nexus Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
1 Juli 2026
Deadline
1 Jul 2027

Job Description

Join Nexus Labs at the forefront of 2026 technological evolution! We're pioneering breakthroughs in quantum-adjacent AI systems and human-computer symbiosis. As an AI Research Scientist, you'll architect next-generation neural architectures that redefine machine cognition. Our state-of-the-art lab in San Francisco offers unparalleled resources to transform theoretical concepts into real-world applications that will shape the next decade.

We believe in radical collaboration across disciplines. You'll partner with neuroscientists, quantum engineers, and ethical AI specialists to develop frameworks for AGI alignment and explainable AI. Our culture embraces calculated risk-taking and celebrates paradigm-shifting discoveries.

Responsibilities

  • Design and implement novel deep learning architectures for quantum-enhanced neural networks
  • Lead research initiatives in human-AI symbiosis and brain-computer interfaces
  • Develop ethical frameworks for autonomous decision-making systems
  • Collaborate with cross-functional teams to prototype 2026-era AI applications
  • Publish findings in top-tier journals and present at global AI conferences
  • Secure external funding through NSF and DARPA grants
  • Mentor junior researchers in emerging AI paradigms

Qualifications

  • PhD in Computer Science, AI, or related field with 3+ years industry experience
  • Proven expertise in transformer architectures and quantum machine learning
  • Publication record at NeurIPS/ICML/ICLR or equivalent venues
  • Proficiency in PyTorch/TensorFlow with distributed training expertise
  • Strong background in computational neuroscience or cognitive modeling
  • Experience with neuromorphic computing hardware (e.g., Loihi, IBM TrueNorth)
  • Demonstrated ability to translate research into production-grade systems

Required Skills

Artificial Intelligence Machine Learning Quantum Computing Neural Networks Deep Learning PyTorch TensorFlow Research Ethics Neuro-Inspired Computing

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