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2026 AI Research Scientist

QuantumLeap Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
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 AI systems that will redefine industries by 2026, and we need visionary researchers to lead this charge. Our state-of-the-art facility in San Francisco offers unparalleled resources for breakthrough research in quantum computing, neural networks, and autonomous systems. Collaborate with Nobel laureates and industry disruptors while shaping the future of artificial intelligence. Enjoy competitive benefits, flexible work arrangements, and opportunities to publish groundbreaking research in top-tier journals.

Responsibilities

  • Design and implement cutting-edge AI algorithms targeting 2026 technological milestones
  • Lead research projects in quantum machine learning and neuromorphic computing
  • Publish peer-reviewed papers and present findings at premier AI conferences
  • Collaborate with engineering teams to translate research into production-ready solutions
  • Mentor junior researchers and foster a culture of innovation
  • Secure external funding through government grants and industry partnerships
  • Stay ahead of emerging AI trends and regulatory landscapes post-2025

Qualifications

  • PhD in Computer Science, AI, or related field with 3+ years research experience
  • Proven track record of publishing in top-tier AI/ML venues (NeurIPS, ICML, etc.)
  • Expertise in deep learning frameworks (PyTorch, TensorFlow) and quantum computing
  • Strong background in reinforcement learning and neural architecture search
  • Experience with large-scale distributed computing and GPU acceleration
  • Demonstrated ability to secure research funding (NSF, DARPA, corporate)
  • Excellent communication skills and ability to collaborate across disciplines

Required Skills

Machine Learning Quantum Computing Deep Learning Research Python PyTorch TensorFlow Reinforcement Learning Neural Networks

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