Job Description
Join QuantumLeap Dynamics at the forefront of technological evolution. We're seeking visionary Quantum Machine Learning Engineers to architect the next generation of AI systems that leverage quantum computing paradigms. Shape the future of artificial intelligence while working with cutting-edge hardware and algorithms in our state-of-the-art R&D facility.
As a pioneer in this emerging field, you'll collaborate with Nobel laureates and top-tier researchers to develop hybrid quantum-classical models that solve previously impossible computational challenges. This role offers unparalleled opportunities to publish groundbreaking research and contribute to humanity's technological leap into 2026 and beyond.
Responsibilities
- Design and implement quantum machine learning algorithms for optimization, simulation, and pattern recognition
- Develop hybrid quantum-classical neural architectures for enterprise-scale AI applications
- Collaborate with quantum hardware teams to optimize algorithms for specific quantum processor constraints
- Create simulation frameworks to validate quantum ML models before hardware deployment
- Lead research initiatives in quantum neural networks and quantum-enhanced deep learning
- Mentor junior researchers and publish findings in top-tier scientific journals
- Translate theoretical quantum computing concepts into practical ML solutions
Qualifications
- PhD in Quantum Computing, Machine Learning, or related field (MS with exceptional experience)
- Proficiency in quantum programming frameworks (Qiskit, Cirq, or PennyLane)
- Expertise in deep learning frameworks (PyTorch/TensorFlow) and classical ML algorithms
- Published research in quantum machine learning or quantum computing
- Strong mathematical foundation in linear algebra, probability, and quantum mechanics
- Experience with cloud quantum computing platforms (IBM Quantum, Amazon Braket)
- Track record of solving complex optimization problems using ML techniques