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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Scientist

Nexus Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
20 Mei 2026
Deadline
20 Mei 2027

Job Description

Join Nexus Innovations at the forefront of technological evolution as we pioneer solutions for 2026 and beyond. We're seeking an AI Research Scientist to architect the next generation of intelligent systems that will redefine industries. In this role, you'll collaborate with Nobel laureates and industry disruptors to develop breakthrough algorithms in quantum computing, neural networks, and autonomous decision-making. Our state-of-the-art incubator in San Francisco offers unparalleled resources to transform theoretical concepts into real-world applications.

You'll lead cross-functional teams in building scalable AI frameworks that process petabytes of data while maintaining ethical integrity. This position includes competitive equity packages, flexible work arrangements, and dedicated research budgets for conference attendance and patent filings.

Responsibilities

  • Design and implement novel machine learning architectures for predictive analytics and autonomous systems
  • Lead research initiatives in quantum machine learning and neuromorphic computing
  • Collaborate with hardware engineers to optimize AI-ASIC co-design for 2026-era infrastructure
  • Publish findings in top-tier journals (Nature, Science, NeurIPS) and present at global conferences
  • Mentor junior researchers and develop patent portfolios for core AI innovations
  • Ensure all research aligns with evolving ethical frameworks for AGI development

Qualifications

  • Ph.D. in Computer Science, AI, or Computational Neuroscience with 5+ years industry experience
  • Expertise in transformer architectures, reinforcement learning, and federated learning
  • Published record in top-tier AI/ML conferences (ICML, ICLR, CVPR)
  • Proficiency in PyTorch/TensorFlow with C++ optimization experience
  • Demonstrated success in deploying production-level ML systems at scale
  • Strong background in computational complexity theory and algorithmic efficiency
  • Experience with quantum computing frameworks (Qiskit, Cirq) preferred

Required Skills

Artificial Intelligence Machine Learning Deep Learning Quantum Computing Neural Networks PyTorch TensorFlow Reinforcement Learning Algorithm Design Research

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