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Information Technology 🏢 Full Time ⭐️ Verified

Futurist AI Research Scientist

QuantumLeap Dynamics
Austin
Estimated Salary
USD 185.000 – USD 275.000
Live Update
14 Mei 2026
Deadline
14 Mei 2027

Job Description

Join QuantumLeap Dynamics at the forefront of technological evolution as we pioneer solutions for 2026 and beyond. We're seeking visionary AI Research Scientists to develop transformative systems that will redefine human-machine interaction. Our Austin-based innovation hub offers unparalleled resources to accelerate your research, including quantum computing access and a $50M R&D fund. This role represents your opportunity to shape the future while enjoying competitive benefits, flexible work arrangements, and a culture that celebrates intellectual curiosity.

Responsibilities

  • Lead research initiatives in generative AI and neural network optimization for 2026-era applications
  • Design and implement novel algorithms for autonomous decision-making systems
  • Collaborate with cross-disciplinary teams to integrate AI solutions with emerging hardware
  • Publish breakthrough research in top-tier AI conferences and journals
  • Develop ethical frameworks for advanced AI deployment in regulated industries
  • Mentor junior researchers and establish best practices for next-gen AI development

Qualifications

  • PhD in Computer Science, AI, or related field with 5+ years industry experience
  • Proven expertise in transformer architectures and large-scale language models
  • Publication record at NeurIPS/ICML/ICLR or equivalent tier conferences
  • Strong background in quantum computing principles or neuromorphic engineering
  • Experience with ethical AI governance frameworks (e.g., EU AI Act alignment)
  • Proficiency in PyTorch/TensorFlow and distributed training environments
  • Demonstrated ability to translate research into production-scale systems

Required Skills

Artificial Intelligence Machine Learning Quantum Computing Neural Networks Generative AI Ethical AI Research & Development PyTorch TensorFlow

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