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2026 AI Research Scientist

QuantumLeap Labs
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

Join QuantumLeap Labs at the forefront of 2026's technological revolution. We're pioneering next-generation AI systems that will redefine human-machine interaction. As our 2026 AI Research Scientist, you'll architect breakthrough solutions in quantum-enhanced machine learning and autonomous decision-making frameworks. Collaborate with Nobel laureates and disrupt industries from healthcare to climate modeling. Our culture thrives on audacious innovation with unparalleled resources—including quantum computing clusters and neuro-symbolic AI labs. If you dream in algorithms and breathe data, this is where your legacy begins.

Responsibilities

  • Design and implement cutting-edge AI architectures leveraging quantum computing principles
  • Lead research in explainable AI and ethical machine learning frameworks
  • Develop autonomous systems for predictive analytics in climate and healthcare domains
  • Author peer-reviewed publications for top-tier AI conferences (NeurIPS, ICML)
  • Mentor junior researchers in advanced neural network optimization techniques
  • Collaborate with product teams to commercialize research breakthroughs
  • Secure federal grants for next-generation AI initiatives

Qualifications

  • PhD in Computer Science, AI, or Quantum Computing (or equivalent experience)
  • 5+ years in research-level machine learning with publications at NeurIPS/ICML
  • Expertise in PyTorch/TensorFlow and quantum programming frameworks (Qiskit, Cirq)
  • Proven track record of deploying production-grade AI systems at scale
  • Deep understanding of transformer architectures and diffusion models
  • Experience with neuromorphic computing and spiking neural networks
  • Strong background in AI ethics and bias mitigation techniques
  • Ability to secure $1M+ in research funding annually

Required Skills

Quantum Computing Machine Learning PyTorch TensorFlow Qiskit Explainable AI Neural Networks AI Ethics Research Publication

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