Job Description
Architecting the Future of 2026
Are you ready to define the technological landscape of tomorrow? Horizon Nexus is seeking a visionary Senior Quantum AI Engineer to lead our 'Project 2026' initiative. We are building the world's first commercially viable hybrid quantum-neural network designed to solve complex global challenges.
In this pivotal role, you will bridge the gap between classical machine learning and emerging quantum computing paradigms. You won't just be writing code; you will be pioneering the infrastructure that will underpin the next decade of technological advancement.
What You Will Do
As a key member of our R&D division, you will:
- Design and Deploy: Architect scalable quantum algorithms that interface seamlessly with classical deep learning frameworks like TensorFlow and PyTorch.
- Pioneering Research: Explore the intersection of quantum mechanics and artificial intelligence to enhance predictive modeling and optimization tasks.
- System Integration: Lead the integration of quantum processing units (QPUs) into our existing cloud infrastructure, ensuring high availability and low latency.
- Team Leadership: Mentor a team of brilliant engineers and data scientists, fostering a culture of innovation and rigorous scientific inquiry.
- Roadmap Definition: Define the technical roadmap for Project 2026, identifying key milestones and delivering technical proofs-of-concept.
Who You Are
We are looking for a thought leader with a passion for the impossible. You possess a deep understanding of both theoretical computer science and practical engineering.
- Education: PhD or Master’s degree in Computer Science, Mathematics, Physics, or a related field.
- Experience: 5+ years of experience in AI/ML, with a strong focus on high-performance computing or quantum computing.
- Technical Skills: Proficiency in Python, C++, CUDA, and familiarity with quantum software stacks (Qiskit, Cirq, or similar).
- Problem Solving: Ability to tackle complex, multi-disciplinary problems with creative and robust solutions.
- Communication: Excellent ability to translate complex technical concepts for both technical and non-technical stakeholders.
Responsibilities
- Design and implement hybrid quantum-classical neural network architectures.
- Optimize quantum circuits for NISQ (Noisy Intermediate-Scale Quantum) devices.
- Collaborate with hardware engineers to improve quantum hardware reliability.
- Conduct research on novel quantum algorithms for optimization and machine learning.
- Ensure code quality, documentation, and adherence to software engineering best practices.
Qualifications
- Ph.D. in Computer Science, Physics, or Mathematics (or equivalent industry experience).
- Proven track record of publishing research or shipping production-level AI systems.
- Deep expertise in Python, C++, and parallel computing.
- Familiarity with cloud platforms (AWS, Azure) and containerization (Docker, Kubernetes).
- Experience with quantum simulators and actual quantum hardware access.
- Strong analytical and problem-solving skills with a focus on innovation.