AI Researcher – Quantum Computing Algorithms

AI Researcher – Quantum Computing Algorithms Key Responsibilities *** this position only open for experienced engineer with Quantum Computing Algorithms*** * Research and prototype quantum-native machine learning models, such as Quantum Neural Networks (QNNs), variational quantum circuits, and quantum-enhanced transformers. * Explore hybrid classical-quantum systems: e.g., using quantum layers in PyTorch or JAX pipelines. * Collaborate on quantum kernel methods, quantum Boltzmann machines, and generative models for data with quantum structure. * Contribute to open-source libraries (e.g., Qiskit, PennyLane, Cirq, TensorFlow Quantum) with new model blocks or benchmarks. * Simulate algorithms on quantum emulators and test performance on real quantum hardware (IBM Q, Rigetti, IonQ, etc.). * Stay ahead of quantum hardware roadmaps and model scalability trends. Required Qualifications * PhD in Physics, Computer Science, Quantum Information, or related field. * Hands-on experience with quantum programming (e.g., Qiskit, PennyLane, Cirq, Braket). * Strong background in machine learning or deep learning, including experience with PyTorch/JAX/TF. * Understanding of quantum circuit design, variational algorithms (VQE, QAOA), and entanglement-based computing. * Experience simulating quantum systems and implementing noise-aware training. Preferred Skills * Experience building hybrid quantum-classical deep learning architectures. * Familiarity with quantum-inspired classical models (e.g., tensor networks, low-rank factorization). * Contributions to open-source quantum ML frameworks or community benchmarks. * Understanding of hardware-specific constraints (connectivity, coherence time, gate depth).