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AI Research Scientist 2026

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

Job Description

Join QuantumLeap Labs at the forefront of 2026's technological revolution! We're seeking visionary AI Research Scientists to pioneer next-generation artificial intelligence systems that will redefine industries. In this cutting-edge role, you'll develop novel algorithms, collaborate with world-class teams, and create solutions that solve humanity's greatest challenges. Our state-of-the-art lab offers unparalleled resources to transform theoretical concepts into real-world applications. If you're passionate about shaping the future of AI and thrive in an environment where innovation is rewarded, this is your opportunity to make history.

Responsibilities

  • Design and implement advanced AI architectures for autonomous systems
  • Lead research initiatives in quantum machine learning and neural networks
  • Collaborate with cross-functional teams to develop scalable AI solutions
  • Publish breakthrough research in top-tier AI conferences and journals
  • Prototype and validate AI models using quantum computing platforms
  • Drive innovation in ethical AI frameworks and responsible AI deployment
  • Mentor junior researchers and contribute to our technical culture

Qualifications

  • PhD in Computer Science, AI, or related field with 3+ years research experience
  • Expertise in deep learning frameworks (TensorFlow, PyTorch) and quantum computing
  • Published record in top-tier AI/ML conferences (NeurIPS, ICML, etc.)
  • Strong background in reinforcement learning and unsupervised learning
  • Experience with large-scale distributed computing and GPU optimization
  • Proficiency in Python, C++, and high-performance computing environments
  • Demonstrated ability to translate research into production systems

Required Skills

AI Research Machine Learning Quantum Computing Deep Learning Neural Networks TensorFlow PyTorch Reinforcement Learning Distributed Computing

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