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AI Research Scientist (2026 Vision)

NeuraCore Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
12 Juli 2026
Deadline
12 Jul 2027

Job Description

Join NeuraCore Dynamics at the forefront of technological evolution. We're pioneering breakthrough AI systems that will redefine industries by 2026. As an AI Research Scientist, you'll architect next-generation neural networks and quantum-inspired algorithms that power autonomous decision-making systems. Collaborate with Nobel laureates and disruptors in our state-of-the-art Silicon Valley incubator. Your work will directly influence the trajectory of human-machine symbiosis, solving complex challenges in healthcare, climate modeling, and autonomous systems. We offer unparalleled resources, including dedicated quantum computing clusters and unrestricted R&D budgets.

Responsibilities

  • Design and implement novel AI architectures for 2026-era autonomous systems
  • Lead cross-functional teams in developing quantum-inspired machine learning models
  • Publish groundbreaking research in top-tier AI conferences (NeurIPS, ICML)
  • Translate theoretical innovations into scalable production-ready systems
  • Collaborate with neuroscientists to develop brain-inspired computing paradigms
  • Secure federal grants for advanced AI research initiatives
  • Mentor PhD candidates in next-generation AI methodologies

Qualifications

  • PhD in Computer Science, AI, or related field with 3+ years post-doc experience
  • Proven track record publishing in top AI/neuroscience journals
  • Expertise in transformer architectures, reinforcement learning, and quantum computing
  • Strong programming skills in Python, PyTorch, and quantum SDKs
  • Experience with large-scale distributed computing frameworks
  • Demonstrated ability to secure NSF/DARPA grants
  • Deep understanding of ethical AI frameworks and bias mitigation
  • Previous startup or industry R&D leadership experience

Required Skills

Machine Learning Quantum Computing Neural Networks Python PyTorch TensorFlow Reinforcement Learning Quantum Algorithms Distributed Systems AI Ethics Research Leadership

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