Job Description
Join QuantumLeap Technologies at the forefront of innovation! We're seeking a visionary AI Research Scientist to pioneer quantum AI solutions that will redefine technology by 2026. This role offers an unparalleled opportunity to shape the future of artificial intelligence through groundbreaking research and development.
As a key member of our Quantum AI division, you'll collaborate with Nobel laureates and industry pioneers to develop next-generation algorithms that leverage quantum computing's exponential power. You'll lead projects with transformative potential in drug discovery, climate modeling, and autonomous systems.
What You'll Achieve:
- Architect quantum neural networks outperforming classical AI by 1000x
- Develop patent-pending algorithms for quantum machine learning
- Lead cross-functional teams in building scalable quantum AI infrastructure
- Publish research in top-tier journals (Nature, Science, NeurIPS)
Responsibilities
- Design and implement novel quantum AI algorithms leveraging quantum entanglement and superposition
- Lead research in quantum machine learning frameworks for 2026-era applications
- Collaborate with quantum hardware teams to optimize algorithms for 1000+ qubit processors
- Develop hybrid quantum-classical AI models solving previously intractable problems
- Secure $5M+ in research grants for quantum AI initiatives
- Mentor PhD researchers and publish 2+ papers annually
- Translate theoretical breakthroughs into production-ready quantum AI systems
Qualifications
- PhD in Quantum Computing, Machine Learning, or Computational Physics with 5+ years industry experience
- Published research in quantum AI or quantum algorithms (Nature/Science/NeurIPS)
- Expertise in Qiskit, Cirq, or similar quantum programming frameworks
- Proven track record developing production-level AI systems using TensorFlow/PyTorch
- Deep understanding of quantum error correction and fault-tolerant architectures
- Experience securing government/private research grants ($1M+ preferred)
- Strong background in complex mathematical optimization and linear algebra