Job Description
At 2026, we are not merely predicting the future; we are architecting it. As a pioneering force in the realm of Quantum AI, we are building the foundational infrastructure for the next decade of technological evolution. We are seeking a visionary Senior Quantum AI Engineer to lead our research and development efforts in bridging the gap between classical machine learning and quantum supremacy.
In this role, you will be at the helm of deploying cutting-edge algorithms on emerging quantum processors, optimizing deep learning models for quantum environments, and defining the standards of performance for the year 2026 and beyond. If you are driven by the challenge of solving the unsolvable and are ready to define the future of computation, 2026 is your destination.
Responsibilities
- Architect Quantum Algorithms: Design and implement advanced quantum machine learning algorithms that outperform classical counterparts in speed and accuracy.
- Roadmap Leadership: Define the technical roadmap for 2026’s quantum integration, ensuring scalability and reliability across distributed systems.
- Model Optimization: Transpile and optimize deep learning models (TensorFlow/PyTorch) to run efficiently on hybrid quantum-classical hardware.
- Research & Development: Conduct cutting-edge research in quantum error correction, variational circuits, and neural network architecture.
- Collaboration: Partner with cross-functional teams of physicists, data scientists, and software engineers to deliver next-gen AI solutions.
- Mentorship: Guide junior engineers and researchers, fostering a culture of innovation and technical excellence within the 2026 team.
Qualifications
- Education: Master’s or PhD in Computer Science, Physics, Mathematics, or a related field with a focus on Quantum Computing or AI.
- Experience: 5+ years of experience in software engineering, with at least 2 years specifically in Machine Learning or Deep Learning.
- Technical Skills: Proficiency in Python, C++, and quantum programming frameworks (Qiskit, Cirq, or Pennylane).
- Understanding: Deep understanding of quantum mechanics principles, linear algebra, and probability theory as applied to AI.
- Problem Solving: Proven track record of solving complex, ambiguous technical problems with innovative solutions.
- Communication: Excellent ability to communicate complex technical concepts to both technical and non-technical stakeholders.