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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Scientist

QuantumLeap Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
13 Mei 2026
Deadline
13 Mei 2027

Job Description

Join QuantumLeap Dynamics at the forefront of artificial intelligence innovation! We're seeking visionary AI Research Scientists to architect next-generation solutions that will redefine industries by 2026. Our dynamic team operates at the intersection of quantum computing, neural networks, and predictive analytics. Collaborate with Nobel laureates and industry pioneers in our state-of-the-art San Francisco lab, where your breakthroughs will directly shape humanity's technological future. We offer unparalleled resources, competitive compensation, and the autonomy to explore groundbreaking research domains.

Responsibilities

  • Design and implement cutting-edge AI models leveraging quantum-inspired algorithms
  • Lead research initiatives in explainable AI and ethical machine learning frameworks
  • Develop proprietary NLP architectures for next-generation conversational AI
  • Collaborate with hardware teams to optimize AI-quantum hybrid systems
  • Publish findings in top-tier journals and present at global conferences
  • Mentor junior researchers and foster cross-disciplinary innovation

Qualifications

  • PhD in Computer Science, AI, or related field with 5+ years research experience
  • Expertise in deep learning frameworks (PyTorch, TensorFlow) and quantum computing principles
  • Proven track record of publishing in NeurIPS, ICML, or Nature Machine Intelligence
  • Mastery of distributed computing (Spark, Kubernetes) and high-performance optimization
  • Strong background in reinforcement learning and generative adversarial networks
  • Experience with MLOps and productionizing large-scale AI systems
  • Exceptional problem-solving skills and ability to communicate complex concepts

Required Skills

Artificial Intelligence Machine Learning Quantum Computing Deep Learning Python PyTorch TensorFlow NLP Reinforcement Learning Distributed Systems MLOps

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