Job Description
We are building the infrastructure for the year 2026 and beyond. Nexus Horizon Labs is seeking a visionary Senior AI & Quantum Architect to lead the development of our next-generation, hybrid neural-quantum computing systems. If you are passionate about pushing the boundaries of what is possible in artificial intelligence and possess a deep understanding of quantum mechanics, we want to meet you.
In this role, you will not just write code; you will design the future of computation. You will bridge the gap between classical machine learning and emerging quantum algorithms, ensuring our solutions are scalable, secure, and ready for the enterprise of tomorrow.
Responsibilities
- Architectural Leadership: Design and implement robust, scalable architectures for hybrid AI-Quantum systems that can handle massive data sets with unprecedented processing speeds.
- R&D Innovation: Lead research initiatives focused on error correction, qubit optimization, and neural network integration to ensure readiness for deployment by 2026.
- System Integration: Oversee the integration of quantum processors with classical cloud infrastructure, ensuring seamless data flow and low-latency operations.
- Team Mentorship: Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence within the engineering division.
- Performance Optimization: Continuously monitor system performance, identifying bottlenecks, and optimizing code for maximum efficiency on next-gen hardware.
- Strategic Planning: Collaborate with product and executive leadership to define technical roadmaps and ensure alignment with the company's long-term vision for 2026.
Qualifications
- Education: Master’s or PhD in Computer Science, Physics, Applied Mathematics, or a related field, with a focus on Quantum Computing or Artificial Intelligence.
- Experience: 7+ years of experience in software engineering, with at least 3 years specifically in AI/ML architecture or Quantum Information Science.
- Technical Skills: Proficiency in Python, C++, CUDA, and familiarity with quantum programming frameworks such as Qiskit, Cirq, or PennyLane.
- Knowledge: Deep understanding of quantum algorithms (QAOA, VQE) and classical machine learning models (TensorFlow, PyTorch).
- Problem Solving: Demonstrated ability to solve complex, interdisciplinary problems at the intersection of physics and computer science.
- Communication: Excellent verbal and written communication skills, capable of translating complex technical concepts for diverse audiences.