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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Scientist (2026 Vision)

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

Job Description

Shape the future at QuantumLeap Labs as we pioneer the next wave of AI innovation for 2026. We're seeking visionary AI Research Scientists to develop transformative solutions that will redefine industries. Join our elite team in San Francisco, where you'll collaborate with Nobel laureates and industry pioneers to push the boundaries of machine learning, neural networks, and quantum-inspired algorithms.

This role offers unparalleled resources, including our $500M 2026 Innovation Fund and access to our quantum computing cluster. You'll lead groundbreaking research with real-world impact, publishing in top-tier journals and presenting at premier global conferences.

Responsibilities

  • Design and implement novel AI architectures for next-generation autonomous systems
  • Lead cross-functional projects combining quantum computing with classical ML models
  • Develop ethical AI frameworks for responsible deployment in regulated industries
  • Collaborate with product teams to translate research into scalable commercial solutions
  • Author breakthrough publications in top-tier AI/ML journals and conferences
  • Mentor junior researchers and foster innovation through our 2026 Incubator Program

Qualifications

  • PhD in Computer Science, AI, or related field with 3+ years of research experience
  • Published record in NeurIPS, ICML, or equivalent tier-1 conferences
  • Expertise in transformer architectures, reinforcement learning, and generative models
  • Proficiency in PyTorch/TensorFlow and distributed computing frameworks
  • Strong background in ethical AI development and bias mitigation
  • Experience with quantum machine learning algorithms and hardware integration
  • Demonstrated ability to lead multi-disciplinary research teams

Required Skills

Machine Learning Quantum Computing Neural Networks AI Ethics PyTorch Reinforcement Learning Generative AI Distributed Computing

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