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AI Research Scientist (2026 Cohort)

QuantumLeap Labs
San Francisco
Estimated Salary
USD 160.000 – USD 220.000
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

Join QuantumLeap Labs at the forefront of artificial intelligence innovation as we prepare for our 2026 research cohort. We're seeking visionary AI Research Scientists to develop breakthrough solutions in quantum machine learning and next-gen neural architectures. Our state-of-the-art lab in San Francisco offers unparalleled resources to transform theoretical concepts into real-world applications that will redefine technological boundaries.

As a pioneer in this exclusive 2026 program, you'll collaborate with Nobel laureates and industry disruptors to tackle humanity's grandest challenges. We provide competitive compensation, equity packages, and a relocation stipend for exceptional candidates. This is your chance to shape the AI landscape of tomorrow.

Responsibilities

  • Design and implement novel quantum machine learning algorithms
  • Lead cross-functional teams in developing next-gen neural network architectures
  • Publish groundbreaking research in top-tier AI/ML conferences (NeurIPS, ICML, etc.)
  • Translate theoretical models into scalable production systems
  • Collaborate with quantum computing teams to hybridize classical and quantum AI approaches
  • Mentor junior researchers and contribute to patent development

Qualifications

  • PhD in Computer Science, Machine Learning, or related field (or equivalent experience)
  • 3+ years of applied research experience in quantum computing or advanced ML
  • Proficiency in Python, TensorFlow/PyTorch, and quantum programming frameworks
  • Published research in top-tier AI/ML conferences (NeurIPS, ICML, etc.)
  • Deep understanding of quantum algorithms and quantum machine learning principles
  • Strong track record of translating research into production systems
  • Experience with distributed computing frameworks (Spark, Kubernetes)

Required Skills

Quantum Computing Machine Learning Deep Learning Python TensorFlow PyTorch Quantum Algorithms Neural Networks Distributed Systems

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