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AI Research Scientist - 2026 Vision

Nexus Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

Join Nexus Innovations at the forefront of technological evolution as we shape the future of AI. We seek a visionary AI Research Scientist to pioneer breakthroughs in quantum machine learning and autonomous systems for 2026 and beyond. This role offers unparalleled opportunities to work with Nobel laureates and industry disruptors in our state-of-the-art San Francisco lab.

What You'll Achieve: Lead research initiatives that will redefine human-computer interaction, develop patent-pending algorithms for next-gen neural networks, and collaborate with Fortune 500 partners deploying your innovations in real-world applications.

Our Culture: We thrive on intellectual curiosity and offer competitive equity packages, flexible work arrangements, and dedicated R&D budgets for your most ambitious projects.

Responsibilities

  • Design and implement novel AI architectures for 2026-era computational challenges
  • Lead cross-functional research teams in publishing breakthrough papers at NeurIPS/ICML
  • Develop ethical frameworks for autonomous decision-making systems
  • Translate theoretical research into scalable production-grade solutions
  • Collaborate with product teams to commercialize research outcomes
  • Secure $5M+ in federal and private research grants
  • Mentor junior researchers and build university partnerships

Qualifications

  • PhD in Computer Science, Machine Learning, or related field
  • 5+ years of experience in cutting-edge AI research
  • Published record in top-tier AI conferences (NeurIPS, ICML, ICLR)
  • Expertise in quantum computing and neuromorphic systems
  • Proficiency in PyTorch/TensorFlow and distributed computing
  • Strong background in ethics and bias mitigation for AI
  • Track record of commercializing research innovations
  • Experience securing research funding from NSF/NIH/DARPA

Required Skills

Machine Learning Quantum Computing Neural Networks PyTorch TensorFlow Research Ethics Grant Writing Distributed Systems

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