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AI Research Scientist (2026)

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

Job Description

Join QuantumLeap Innovations at the forefront of technological evolution as we pioneer solutions for 2026 and beyond. We're seeking visionary AI Research Scientists to architect next-generation neural networks and quantum-ML hybrids. This role offers unparalleled resources to transform theoretical breakthroughs into real-world applications that will shape humanity's digital future.

Our state-of-the-art lab in San Francisco's innovation district provides an environment where your work directly impacts emerging fields like generative AI ethics, autonomous systems, and predictive climate modeling. Collaborate with Nobel laureates and industry disruptors while enjoying flexible schedules, equity grants, and unlimited R&D budgets.

Responsibilities

  • Design and implement novel AI architectures for 2026-era challenges
  • Lead quantum-ML hybrid research initiatives with 200+ qubit systems
  • Publish breakthrough research in top-tier journals and conferences
  • Develop ethical frameworks for generative AI deployment
  • Mentor cross-functional teams of engineers and data scientists
  • Secure $5M+ in annual research grants and partnerships
  • Present findings at global tech summits including Davos and AI World Congress

Qualifications

  • PhD in Computer Science, AI, or Quantum Computing (or equivalent experience)
  • 5+ years developing production ML systems at FAANG or similar scale
  • Published research in NeurIPS, ICML, or Nature AI
  • Expertise in transformer architectures, reinforcement learning, and NLP
  • Proficiency with TensorFlow/PyTorch and quantum programming frameworks
  • Track record of translating research into commercial products
  • Strong background in AI ethics and responsible AI development
  • Ability to secure competitive research funding

Required Skills

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

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