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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Scientist

NeuroSync Technologies
Austin
Estimated Salary
USD 150.000 – USD 220.000
New
Live Update
12 Juli 2026
Deadline
12 Jul 2027

Job Description

Join NeuroSync Technologies at the forefront of cognitive computing innovation. We're pioneering neural interface systems that will redefine human-machine collaboration by 2026. As an AI Research Scientist, you'll architect breakthrough algorithms for adaptive neural networks, pushing the boundaries of machine cognition and real-time learning systems. Our Austin lab offers unparalleled resources and a culture of relentless innovation.

What You'll Achieve:

  • Design next-gen neural networks with 10x efficiency gains
  • Lead quantum-enhanced machine learning protocols
  • Collaborate with Nobel laureates on ethical AI frameworks
  • Shape patents that will define the 2026 tech landscape

Responsibilities

  • Develop proprietary reinforcement learning architectures for autonomous systems
  • Implement neuromorphic computing solutions for edge AI deployment
  • Optimize federated learning models across distributed quantum nodes
  • Author peer-reviewed publications in Nature AI and IEEE journals
  • Lead cross-functional sprints on neuro-symbolic integration
  • Architect ethical AI governance frameworks for 2026 compliance
  • Mentor PhD fellows in advanced deep learning methodologies

Qualifications

  • PhD in Computer Science, Cognitive Neuroscience, or related field
  • 5+ years developing production-grade neural networks
  • Expertise in PyTorch/TensorFlow with quantum computing APIs
  • Published research at NeurIPS/ICML with 500+ citations
  • Proficiency in neuromorphic hardware (Intel Loihi, IBM TrueNorth)
  • Strong background in cognitive architecture modeling
  • Experience with FDA/ISO AI regulatory frameworks
  • Portfolio of deployed AI systems with measurable impact

Required Skills

Machine Learning Deep Learning Quantum Computing Neural Networks Python TensorFlow Cognitive Architecture Neuromorphic Computing Reinforcement Learning

Ready to Take This Challenge?

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