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AI Research Scientist (2026)

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

Job Description

Step into the future with QuantumLeap Dynamics as we pioneer the next wave of artificial intelligence. We're seeking visionary AI Research Scientists to develop breakthrough technologies that will redefine industries by 2026. Join our elite team in San Francisco, where you'll collaborate with Nobel laureates and industry disruptors to create solutions that solve humanity's most pressing challenges.

We offer unparalleled resources, a culture of radical innovation, and the opportunity to shape the AI landscape for decades to come. Our state-of-the-art lab features quantum computing infrastructure and dedicated research budgets for moonshot projects.

Responsibilities

  • Lead cutting-edge research in next-gen AI architectures (quantum neural networks, self-improving systems)
  • Develop novel algorithms for ethical AI alignment and autonomous decision-making
  • Collaborate with quantum computing teams to hybridize AI and quantum technologies
  • Publish groundbreaking research in top-tier journals and conferences
  • Prototype and validate AI systems with 10x efficiency improvements over current models
  • Mentor junior researchers and contribute to patent development
  • Present findings to C-suite executives and external stakeholders

Qualifications

  • PhD in Computer Science, AI, or related field with 5+ years research experience
  • Published record in NeurIPS, ICML, or equivalent tier conferences
  • Expertise in transformer architectures, reinforcement learning, and generative models
  • Proficiency in Python, TensorFlow/PyTorch, and distributed computing
  • Deep understanding of quantum computing principles and AI-quantum hybrid systems
  • Strong background in AI ethics, bias mitigation, and safety protocols
  • Experience securing $1M+ in research funding or industry partnerships

Required Skills

AI Research Machine Learning Quantum Computing Neural Networks Reinforcement Learning Python TensorFlow PyTorch Ethics AI Safety Quantum Algorithms

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