Job Description
We are pioneering the next generation of artificial intelligence by integrating advanced quantum computing with classical machine learning. As part of our 2026 Strategic Initiative, we are looking for a visionary Senior Quantum AI Research Engineer to lead our R&D efforts in developing scalable, fault-tolerant quantum algorithms.
In this role, you will bridge the gap between theoretical physics and practical software engineering, creating the infrastructure that powers the future of enterprise data processing. If you are passionate about solving complex problems at the intersection of quantum mechanics and AI, this is your opportunity to shape the landscape of 2026 and beyond.
Responsibilities
- Design, implement, and optimize quantum machine learning algorithms tailored for NISQ (Noisy Intermediate-Scale Quantum) devices.
- Lead the architecture for hybrid quantum-classical neural networks to solve complex optimization problems.
- Collaborate with cross-functional teams of physicists, data scientists, and software engineers to translate theoretical research into production-ready code.
- Conduct rigorous testing and validation of quantum circuits to ensure reliability and scalability for 2026 deployment.
- Prepare and submit high-impact research papers to leading conferences and journals.
- Provide mentorship and technical guidance to junior researchers and engineering interns.
- Stay ahead of industry trends in quantum computing, hardware advancements, and AI methodologies.
Qualifications
- PhD or Master’s degree in Computer Science, Physics, Mathematics, or a related field with a focus on Quantum Computing.
- Proven experience (5+ years) in developing quantum algorithms or working with quantum computing frameworks (Qiskit, Cirq, PyQuil, or Amazon Braket).
- Strong proficiency in Python and C++ for high-performance computing and algorithm implementation.
- Deep understanding of linear algebra, probability theory, and statistical mechanics.
- Experience with classical machine learning frameworks (TensorFlow, PyTorch) and integrating them with quantum backends.
- Excellent problem-solving skills and the ability to work in a fast-paced, research-driven environment.
- Strong written and verbal communication skills for technical reporting and stakeholder presentations.