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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Scientist

QuantumLeap Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
Live Update
20 Mei 2026
Deadline
20 Mei 2027

Job Description

Join QuantumLeap Technologies at the forefront of artificial intelligence innovation. We're pioneering breakthroughs in quantum-enhanced machine learning and autonomous systems that will redefine 2026's technological landscape. As an AI Research Scientist, you'll collaborate with world-class experts to develop next-gen algorithms that solve humanity's most complex challenges. Our San Francisco lab offers state-of-the-art facilities and a culture where curiosity drives progress.

We offer competitive compensation, comprehensive benefits, and unparalleled opportunities to shape the future of AI. If you're passionate about pushing boundaries and creating technologies that matter, we want you on our team.

Responsibilities

  • Lead advanced R&D projects in quantum-AI integration and neural network optimization
  • Design and implement novel algorithms for autonomous decision-making systems
  • Collaborate with cross-functional teams to translate research into scalable production models
  • Publish findings in top-tier journals and present at international conferences
  • Mentor junior researchers and contribute to strategic innovation roadmaps
  • Secure and manage research grants from leading tech foundations

Qualifications

  • PhD in Computer Science, Machine Learning, or related field with 5+ years industry experience
  • Expertise in deep learning frameworks (PyTorch, TensorFlow) and quantum computing principles
  • Proven track record of publishing in NeurIPS, ICML, or equivalent tier venues
  • Strong background in reinforcement learning and neural architecture search
  • Experience with large-scale distributed computing environments
  • Exceptional problem-solving skills and ability to innovate in ambiguous domains

Required Skills

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

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