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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Scientist

QuantumLeap Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
22 Mei 2026
Deadline
22 Mei 2027

Job Description

Join QuantumLeap Labs at the forefront of 2026's AI revolution. We're pioneering next-generation neural networks that will redefine human-machine interaction. As an AI Research Scientist, you'll architect breakthrough algorithms while collaborating with Nobel laureates and industry disruptors. Our state-of-the-art lab offers unparalleled resources to transform theoretical concepts into tangible innovations.

We provide competitive equity packages, flexible remote options, and dedicated R&D budgets. Your work will directly impact sectors from healthcare to climate modeling, positioning you as a key architect of tomorrow's technological landscape.

Responsibilities

  • Design and implement novel deep learning architectures for 2026-era applications
  • Lead cross-functional teams in deploying AI solutions at enterprise scale
  • Publish breakthrough research in top-tier AI journals and conferences
  • Develop ethical frameworks for responsible AI deployment
  • Collaborate with quantum computing teams to hybridize classical and quantum AI
  • Secure $1M+ in annual research grants from government and private partners
  • Mentor PhD candidates and junior researchers in advanced ML techniques

Qualifications

  • PhD in Machine Learning, Computer Science, or related field (or equivalent industry experience)
  • 5+ years of experience developing production-level deep learning systems
  • Published record in NeurIPS/ICML/ICLR or equivalent top-tier venues
  • Expertise in transformer architectures, reinforcement learning, and generative models
  • Proficiency in PyTorch, TensorFlow, and distributed computing frameworks
  • Demonstrated success securing competitive research funding
  • Strong background in AI ethics and bias mitigation strategies

Required Skills

Machine Learning Deep Learning Python PyTorch TensorFlow AI Ethics Quantum Computing Research Reinforcement Learning Generative Models

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