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Senior AI Research Scientist

QuantumLeap Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

Join QuantumLeap Labs at the forefront of technological evolution as we pioneer breakthrough AI systems for the 2026 paradigm shift. We're seeking visionary Senior AI Research Scientists to architect the next generation of autonomous intelligence that will redefine human-machine collaboration.

In this pivotal role, you'll lead cutting-edge research in neural architecture optimization and quantum-inspired machine learning. Our state-of-the-art facilities in San Francisco offer unparalleled resources to transform theoretical concepts into scalable solutions that will shape the future of technology.

We offer a competitive compensation package with equity, comprehensive benefits, and the autonomy to explore your most ambitious research ideas. If you're ready to build the AI infrastructure of tomorrow, we want to hear from you.

Responsibilities

  • Design and implement novel neural network architectures for 2026-era autonomous systems
  • Lead cross-functional research teams in developing quantum-enhanced machine learning algorithms
  • Publish breakthrough findings in top-tier AI conferences and journals
  • Collaborate with engineering teams to translate research into production-ready AI solutions
  • Establish ethical frameworks for advanced AI systems with human-centric safety protocols
  • Drive innovation in transfer learning and multimodal intelligence systems
  • Mentor junior researchers and foster a culture of scientific excellence

Qualifications

  • PhD in Computer Science, Machine Learning, or related field with 5+ years industry experience
  • Proven expertise in deep learning frameworks (PyTorch, TensorFlow) and distributed computing
  • Published record in top-tier AI conferences (NeurIPS, ICML, CVPR)
  • Strong background in reinforcement learning and unsupervised learning methodologies
  • Experience with MLOps and deploying large-scale AI systems in production environments
  • Expertise in Python, CUDA, and high-performance computing architectures
  • Demonstrated ability to lead complex research projects from conception to publication

Required Skills

Deep Learning Reinforcement Learning Quantum Computing Neural Architecture Design MLOps PyTorch TensorFlow Distributed Computing Research Leadership

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