Job Description
We are seeking a visionary Quantum Neural Architect to spearhead our research division as we prepare for the technological paradigm shift of 2026. At Horizon Dynamics, we are not merely building software; we are engineering the infrastructure of tomorrow by merging classical deep learning with quantum computing paradigms.
In this role, you will define the architecture for our next-generation AI systems, ensuring they are scalable, secure, and capable of processing exabyte-scale datasets. If you are passionate about the future of intelligence and possess a deep understanding of both quantum mechanics and neural networks, we want you to help us build the future.
Responsibilities
- Design and implement scalable quantum neural network architectures capable of handling complex, multi-modal data streams.
- Bridge the gap between theoretical quantum algorithms and practical, deployable machine learning models.
- Optimize quantum circuit compilation for classical hardware environments to ensure high-throughput inference.
- Lead a team of elite researchers in developing proprietary algorithms for predictive analytics in the 2026 era.
- Conduct rigorous testing on edge devices and supercomputing clusters to validate model stability and security.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Physics, Applied Mathematics, or a related quantitative field with a focus on AI or Quantum Mechanics.
- 5+ years of experience in machine learning engineering, with a strong portfolio involving deep learning frameworks (TensorFlow, PyTorch, JAX).
- Proficiency in quantum programming languages such as Qiskit, Cirq, or PennyLane.
- Deep understanding of optimization algorithms, stochastic processes, and distributed systems.
- Proven track record of publishing in top-tier conferences (NeurIPS, ICML, or relevant quantum physics journals).