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AI Research Scientist - 2026 Vision

QuantumLeap Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
New
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Join QuantumLeap Dynamics at the forefront of 2026's technological revolution! We're pioneering next-generation AI systems that will redefine human-machine interaction. As an AI Research Scientist, you'll architect breakthrough algorithms in quantum computing integration and neural network optimization. Our state-of-the-art lab in San Francisco offers unmatched resources to transform theoretical concepts into reality. What you'll build today powers tomorrow's innovations. We offer competitive equity, flexible hybrid work, and unparalleled growth opportunities in the world's most dynamic tech ecosystem.

Responsibilities

  • Develop novel AI architectures for quantum-classical hybrid computing systems
  • Lead research initiatives in explainable AI (XAI) and ethical algorithm design
  • Collaborate with cross-functional teams to deploy prototypes in production environments
  • Author breakthrough publications in top-tier AI/ML conferences (NeurIPS, ICML, etc.)
  • Mentor junior researchers and drive technical excellence within the lab
  • Secure and manage federal/state grants for frontier AI research projects
  • Translate theoretical models into scalable solutions for real-world applications

Qualifications

  • PhD in Computer Science, AI, or related field with 3+ years industry experience
  • Published record in quantum machine learning or neuromorphic computing
  • Expertise in PyTorch/TensorFlow and high-performance computing frameworks
  • Proven track record of shipping production-level AI systems
  • Deep understanding of transformer architectures and attention mechanisms
  • Familiarity with MLOps tools (MLflow, Kubeflow, etc.)
  • Strong background in theoretical computer science and computational complexity
  • Experience securing DoD/NSF research grants preferred

Required Skills

AI Research Quantum Computing Machine Learning PyTorch TensorFlow MLOps Neural Networks Quantum-Classical Hybrid Systems Explainable AI

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