Job Description
Join QuantumLeap Technologies at the forefront of 2026's technological revolution. We seek an innovative AI Research Scientist to pioneer breakthroughs in quantum machine learning and autonomous systems. Shape the future of human-AI collaboration in our state-of-the-art San Francisco lab, where your work will directly impact how humanity interfaces with emerging technologies. This role offers unparalleled opportunities to publish research, lead cross-functional projects, and contribute to patents that will define the next decade of innovation.
Our team operates at the intersection of neuroscience, quantum computing, and generative AI. You'll collaborate with Nobel laureates and industry disruptors to develop ethical frameworks for superintelligent systems while solving complex challenges in climate modeling and personalized medicine.
Responsibilities
- Design and implement novel quantum neural network architectures for 2026-era computing constraints
- Lead research initiatives in explainable AI and human-compatible machine learning paradigms
- Develop ethical governance frameworks for autonomous decision-making systems
- Publish 3+ high-impact research papers annually in top-tier AI/quantum journals
- Mentor junior researchers and cross-functional teams in cutting-edge AI methodologies
- Translate theoretical research into production-ready solutions for enterprise clients
- Secure $2M+ in annual research funding through federal and private grants
Qualifications
- PhD in Computer Science, Quantum Physics, or related field with 5+ years of research experience
- Expertise in quantum computing algorithms and hybrid quantum-classical systems
- Published record in top-tier AI conferences (NeurIPS, ICML, ICLR) or quantum journals
- Proficiency in Python, TensorFlow/PyTorch, and quantum programming languages (Qiskit, Cirq)
- Demonstrated experience leading multi-year research projects with measurable outcomes
- Strong background in ethical AI development and responsible innovation frameworks
- Ability to communicate complex technical concepts to non-technical stakeholders