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AI/ML Research Scientist (2026 Tech)

Nexus Future Labs
San Francisco
Estimated Salary
USD 190.000 – USD 280.000
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Join Nexus Future Labs at the forefront of 2026's technological revolution. We're pioneering quantum-adjacent AI systems that will redefine human-machine collaboration. As our AI/ML Research Scientist, you'll architect breakthrough algorithms for next-generation autonomous systems, predictive climate models, and neural-computing interfaces. Work in our state-of-the-art lab with a team of Nobel laureates and Turing Award winners, publishing research in Science and Nature while commercializing your innovations through our venture arm.

Why Nexus Future Labs? Our patent-pending 'Neural Scaffold' technology enables real-time brain-AI symbiosis – the very foundation of 2026's cognitive computing landscape. We offer equity grants in our spinout ventures and unlimited research budget with quarterly 'Innovation Sabbaticals' at our Arctic research outpost.

Responsibilities

  • Design quantum-resistant ML architectures for 2026-era autonomous systems
  • Lead cross-disciplinary research in neuromorphic computing and quantum AI
  • Develop predictive models for climate adaptation systems with 99.8% accuracy
  • Commercialize research through patents and product development
  • Mentor PhD candidates in our 'Future Minds' fellowship program
  • Present findings at global forums like Web Summit and TED2026

Qualifications

  • PhD in Computer Science, Quantum Physics, or Computational Neuroscience (2020-2026)
  • Published 5+ papers in top-tier journals (Nature/Science/NeurIPS)
  • Expertise in tensor networks and quantum machine learning frameworks
  • Proficiency in neuromorphic hardware (Loihi, IBM TrueNorth)
  • Experience with climate modeling APIs (NASA Earth Exchange, CERN Open Data)
  • Fluency in Python, TensorFlow Quantum, and PyTorch 2.0+
  • Portfolio demonstrating real-world quantum algorithm implementations

Required Skills

Quantum Computing Neuromorphic AI Climate Modeling Tensor Networks TensorFlow Quantum PyTorch 2.0 Research Commercialization Predictive Analytics

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