Job Description
At Chronos Dynamics, we are not just predicting the future; we are engineering it. As we approach the pivotal year of 2026, the boundaries between quantum mechanics and artificial intelligence are dissolving. We are seeking a visionary Senior Quantum-Neural Architect to lead our R&D division in designing the next generation of hybrid computing systems.
In this role, you will define the architectural standards for the 2026 paradigm shift. You will work directly with top-tier scientists to bridge the gap between theoretical quantum physics and practical, scalable deep learning models. If you are driven by the challenge of building systems that operate beyond classical silicon limits, this is your opportunity to shape the technological landscape of tomorrow.
Why Join Us?
- The 2026 Vision: Work on cutting-edge projects that define the standard for post-silicon computing.
- Autonomy: Lead architectural decisions with significant autonomy and impact.
- Equity Package: Competitive compensation tied to the company's future success.
Responsibilities
- Design and prototype high-level quantum neural network architectures tailored for near-term quantum hardware.
- Develop novel algorithms that optimize quantum circuit depth and error correction strategies for AI inference.
- Collaborate with cross-functional teams to integrate quantum modules into existing deep learning pipelines.
- Conduct rigorous testing and validation of quantum-classical hybrid systems to ensure scalability and stability.
- Stay ahead of industry trends in quantum computing, superconductivity, and neuromorphic engineering.
- Mentor junior researchers and define technical roadmaps for the architecture team.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Physics, Mathematics, or a related technical field with a focus on Quantum Computing or AI.
- Proven experience (5+ years) in designing complex systems, specifically within AI/ML or High-Performance Computing.
- Deep understanding of quantum computing principles (Qubits, superposition, entanglement) and quantum algorithms (Grover, Shor, QAOA).
- Expert proficiency in Python, C++, and frameworks such as PyTorch or TensorFlow.
- Experience with quantum simulators (Qiskit, Cirq, Pennylane) and cloud quantum services (AWS Braket, Google Quantum AI).
- Strong problem-solving skills with the ability to navigate ambiguity in a rapidly evolving technological landscape.
Responsibilities
- Design and prototype high-level quantum neural network architectures tailored for near-term quantum hardware.
- Develop novel algorithms that optimize quantum circuit depth and error correction strategies for AI inference.
- Collaborate with cross-functional teams to integrate quantum modules into existing deep learning pipelines.
- Conduct rigorous testing and validation of quantum-classical hybrid systems to ensure scalability and stability.
- Stay ahead of industry trends in quantum computing, superconductivity, and neuromorphic engineering.
- Mentor junior researchers and define technical roadmaps for the architecture team.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Physics, Mathematics, or a related technical field with a focus on Quantum Computing or AI.
- Proven experience (5+ years) in designing complex systems, specifically within AI/ML or High-Performance Computing.
- Deep understanding of quantum computing principles (Qubits, superposition, entanglement) and quantum algorithms (Grover, Shor, QAOA).
- Expert proficiency in Python, C++, and frameworks such as PyTorch or TensorFlow.
- Experience with quantum simulators (Qiskit, Cirq, Pennylane) and cloud quantum services (AWS Braket, Google Quantum AI).
- Strong problem-solving skills with the ability to navigate ambiguity in a rapidly evolving technological landscape.