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2026 AI Research Scientist

QuantumLeap Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Join QuantumLeap Labs at the forefront of 2026's AI revolution. We're seeking visionary AI Research Scientists to develop next-generation neural architectures that will redefine human-computer interaction. Our Austin-based innovation hub offers unparalleled resources to pioneer breakthroughs in quantum-inspired machine learning, ethical AI frameworks, and autonomous systems. Collaborate with Nobel laureates and industry disruptors in an environment where your ideas shape tomorrow's technological landscape. Enjoy competitive compensation, cutting-edge tools, and the opportunity to patent transformative innovations.

Responsibilities

  • Design and implement novel neural network architectures for 2026-era applications
  • Lead research initiatives in quantum-enhanced machine learning algorithms
  • Develop ethical AI governance frameworks for next-generation autonomous systems
  • Collaborate with cross-functional teams to integrate research into commercial products
  • Publish breakthrough findings in top-tier AI conferences and journals
  • Secure patents for proprietary AI methodologies and systems
  • Mentor junior researchers and foster innovation culture

Qualifications

  • PhD in Computer Science, AI, or related field with 5+ years research experience
  • Proven track record of publishing in NeurIPS/ICML/ICLR venues
  • Expertise in transformer architectures and quantum computing principles
  • Strong programming skills in Python, PyTorch, and TensorFlow
  • Experience with large-scale distributed computing environments
  • Deep understanding of AI ethics and responsible development practices
  • Ability to translate complex research into commercial applications
  • Preferred background in neuromorphic computing or bio-inspired AI

Required Skills

AI Research Machine Learning Quantum Computing Neural Networks Deep Learning Python PyTorch TensorFlow Ethics in AI Distributed Computing

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