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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Scientist - 2026 Visionary

QuantumLeap Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
Live Update
17 Mei 2026
Deadline
17 Mei 2027

Job Description

Join QuantumLeap Innovations at the forefront of 2026's technological revolution! We're seeking an AI Research Scientist to pioneer breakthrough solutions in autonomous systems and human-machine collaboration. Shape the future by developing next-generation AI models that redefine industry standards. Work in our state-of-the-art labs with world-class researchers to solve humanity's most complex challenges.

This role offers unparalleled opportunities to publish in top-tier journals, lead cutting-edge projects, and contribute to patents that will define the next decade. Our collaborative environment encourages bold thinking and rewards innovation.

Responsibilities

  • Design and implement novel AI architectures for 2026-era autonomous systems
  • Lead cross-functional research teams in developing quantum-optimized machine learning models
  • Publish breakthrough research in top-tier AI conferences and journals
  • Collaborate with product teams to translate research into scalable commercial solutions
  • Secure patents and intellectual property for disruptive AI innovations
  • Mentor junior researchers and foster a culture of scientific excellence

Qualifications

  • PhD in Computer Science, AI, or related field with 3+ years research experience
  • Proven expertise in deep learning, reinforcement learning, and neural architecture search
  • Published research in NeurIPS, ICML, or equivalent tier conferences
  • Strong programming skills in Python, PyTorch, and TensorFlow
  • Experience with quantum computing frameworks (Qiskit, Cirq) preferred
  • Demonstrated ability to lead complex research projects from concept to production
  • Passion for ethical AI development and human-centric design principles

Required Skills

AI Research Machine Learning Deep Learning Quantum Computing Neural Networks Python PyTorch TensorFlow Reinforcement Learning Research Publication Ethics in AI

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