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Information Technology 🏢 Full Time ⭐️ Verified

AI/ML Research Scientist

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

Job Description

Join QuantumLeap Labs at the forefront of technological evolution as we pioneer solutions for 2026 and beyond. We're seeking visionary AI/ML Research Scientists to architect next-generation autonomous systems and predictive models that will redefine industries. Our interdisciplinary team operates at the intersection of quantum computing, neural networks, and sustainable AI, offering unparalleled opportunities to publish groundbreaking research and collaborate with Nobel laureates.

Why QuantumLeap? • Equity in patented AI frameworks • Unlimited conference budget • Flexible R&D time allocation • State-of-the-art quantum simulation lab • Health/dental/vision premiums covered at 100%

Responsibilities

  • Design and implement novel ML architectures for edge computing environments
  • Lead research initiatives in explainable AI and ethical algorithm development
  • Collaborate with quantum computing teams to hybridize classical-quantum models
  • Author peer-reviewed publications for top-tier AI conferences (NeurIPS, ICML)
  • Mentor junior researchers through our patent-focused incubation program
  • Translate theoretical frameworks into production-ready prototypes
  • Secure $1M+ in annual research grants through NIH/NSF partnerships

Qualifications

  • PhD in Computer Science, Mathematics, or Physics with 3+ years industry research
  • Published work in top-tier ML conferences (NeurIPS, ICLR) or Nature journals
  • Expertise in PyTorch/TensorFlow with 10B+ parameter model deployment
  • Proficiency in quantum computing frameworks (Qiskit, Cirq) or willingness to learn
  • Track record of open-source contributions with 5k+ GitHub stars
  • Experience with federated learning and differential privacy techniques
  • Strong background in computational complexity theory

Required Skills

Machine Learning Quantum Computing PyTorch Research Ethics TensorFlow Neural Networks Quantum Algorithms Federated Learning Explainable AI

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