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AI Research Scientist (2026)

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

Job Description

Join QuantumLeap Labs at the forefront of 2026's AI revolution! We're seeking visionary AI Research Scientists to pioneer breakthrough technologies that will redefine human-machine interaction. Our Austin-based innovation hub combines cutting-edge research with real-world application, offering unparalleled opportunities to shape the future of artificial intelligence.

In this role, you'll collaborate with world-class researchers to develop next-gen AI systems, from quantum-enhanced neural networks to ethical autonomous frameworks. We provide competitive compensation, flexible work arrangements, and a culture that celebrates intellectual curiosity and bold experimentation.

If you're passionate about solving humanity's greatest challenges through AI and ready to contribute to technologies that will impact billions by 2026, QuantumLeap Labs is your launchpad.

Responsibilities

  • Design and implement advanced AI architectures for 2026-era applications
  • Lead research initiatives in quantum machine learning and neuromorphic computing
  • Develop ethical AI frameworks aligned with emerging global regulations
  • Collaborate with engineering teams to translate research into production systems
  • Publish breakthrough findings in top-tier journals and conferences
  • Mentor junior researchers and foster cross-disciplinary innovation
  • Stay ahead of 2026 technology trends through continuous learning

Qualifications

  • PhD in Computer Science, AI, or related field with 3+ years research experience
  • Expertise in deep learning, reinforcement learning, and probabilistic modeling
  • Proficiency in Python, PyTorch, TensorFlow, and quantum computing frameworks
  • Published research in NeurIPS, ICML, or equivalent tier-1 venues
  • Strong background in AI ethics, bias mitigation, and responsible AI
  • Experience with distributed computing and large-scale model training
  • Proven ability to translate theoretical research into practical applications

Required Skills

Machine Learning Deep Learning Quantum Computing AI Ethics PyTorch TensorFlow Reinforcement Learning Neural Networks

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