Job Description
Are you ready to shape the technological landscape of 2026 and beyond? Nebula Future Systems is seeking a visionary Quantum AI Architect to lead our next-generation research division. In this pivotal role, you will bridge the gap between classical machine learning and quantum computing paradigms, building the foundational algorithms that will power the autonomous systems of tomorrow.
We are looking for a thought leader who is passionate about pushing the boundaries of what is possible in AI, quantum physics, and distributed computing. If you thrive in a fast-paced, innovative environment and want to be at the forefront of the industry's evolution, we want to hear from you.
Responsibilities
- Architect Quantum Algorithms: Design and implement hybrid quantum-classical algorithms capable of solving complex optimization problems and accelerating deep learning models.
- R&D Leadership: Spearhead research initiatives focused on post-2026 AI architectures, exploring novel approaches to neural network efficiency on quantum hardware.
- System Integration: Oversee the integration of quantum processing units (QPUs) into our existing cloud infrastructure, ensuring seamless interoperability.
- Team Mentorship: Guide a cross-functional team of data scientists, physicists, and software engineers, fostering a culture of innovation and technical excellence.
- Strategic Roadmapping: Define the technical roadmap for our quantum AI initiatives, aligning them with long-term business objectives and industry trends.
Qualifications
- Education: Master’s or PhD in Computer Science, Physics, Mathematics, or a related field with a focus on Quantum Information Science or Machine Learning.
- Experience: At least 7 years of experience in software engineering, with 3+ years specifically in quantum computing or advanced AI systems.
- Technical Skills: Proficiency in Python, C++, and frameworks such as Qiskit, Cirq, or Pennylane; deep understanding of TensorFlow/PyTorch.
- Problem Solving: Proven track record of solving complex technical challenges and the ability to think abstractly about computational theory.
- Communication: Exceptional ability to communicate complex technical concepts to both technical and non-technical stakeholders.