Published research paper on training specialized LLMs for quantum computing code generation using Qiskit. Addresses unique challenges in quantum programming, including scarcity of quantum code examples and rapid field evolution. Our model outperforms existing state-of-the-art quantum computing models.
Published research demonstrating integration of Reinforcement Learning into quantum transpiling workflows for Qiskit transpiler service. Achieves near-optimal circuit synthesis and routing with significant performance improvements over traditional optimization methods, handling Linear Function, Clifford, and Permutation circuits up to 65 qubits.
Extremely proud of the massive Qiskit SDK v1.0 release including two projects from my team: the Qiskit Transpiler with AI transpiling passes and the Qiskit Code Assistant. This full-stack software for quantum computing brings together cutting-edge AI and quantum technologies.
IBM Quantum team recruiting AI Engineer interns based in Spain to work on introducing new AI-based capabilities in the software stack, including AI circuit transpilers compatible with Qiskit and LLM-powered code assistants. Interns will support AI model training, deployment, software service development, and MLOps work.