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AI Research Scientist (2026 Vision)

QuantumLeap Labs
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
New
Live Update
13 Mei 2026
Deadline
13 Mei 2027

Job Description

Shape the future at QuantumLeap Labs, where we're pioneering breakthroughs in quantum-AI hybrid systems for 2026. As an AI Research Scientist, you'll architect next-generation algorithms that redefine computational boundaries. Join our elite team of visionaries working on projects that will transform industries—from autonomous biotech to climate modeling. We offer unparalleled resources, a culture of relentless innovation, and the opportunity to leave an indelible mark on technological evolution.

Your work will directly impact our 2026 roadmap, developing scalable AI solutions that solve humanity's most complex challenges. Collaborate with Nobel laureates, access state-of-the-art quantum computing infrastructure, and lead research that bridges theoretical breakthroughs with real-world applications. This isn't just a role—it's your chance to engineer tomorrow, today.

Responsibilities

  • Design and implement cutting-edge AI algorithms for quantum-enhanced machine learning systems
  • Lead cross-functional research initiatives focused on 2026 technology roadmap milestones
  • Develop novel neural architectures optimized for quantum computing environments
  • Collaborate with hardware engineers to co-design AI-quantum hybrid systems
  • Publish breakthrough research in top-tier journals/conferences (NeurIPS, ICML, Nature)
  • Mentor junior researchers and drive innovation through weekly tech sprints
  • Secure external funding through NSF/NIH grants for 2026-forward projects

Qualifications

  • PhD in Computer Science, Quantum Physics, or related field (or equivalent industry impact)
  • 5+ years in AI/ML research with 2+ publications in top-tier venues
  • Expertise in quantum computing frameworks (Qiskit, Cirq) and deep learning frameworks
  • Proven track record of deploying production-level AI systems at scale
  • Strong background in computational complexity theory and algorithmic optimization
  • Experience with high-performance computing (HPC) and distributed ML systems
  • Demonstrated ability to translate theoretical research into commercial applications

Required Skills

Quantum Computing Machine Learning Neural Architecture Search High-Performance Computing Algorithmic Optimization Qiskit TensorFlow Research Distributed Systems

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