Job Description
At QuantumCore Systems, we are not just predicting the future; we are architecting it. We are launching the Project 2026 Initiative, a massive undertaking to revolutionize artificial general intelligence through quantum supremacy. We are looking for a visionary Senior AI & Quantum Architect to lead our R&D division. If you thrive in high-pressure environments and are passionate about the intersection of quantum mechanics and deep learning, this is your opportunity to leave a legacy. Join us in defining the technological landscape of the 2026 era.
Responsibilities
- Design and architect scalable quantum neural network architectures tailored for Project 2026.
- Lead the research and development of proprietary algorithms that bridge classical AI and quantum computing.
- Oversee the implementation of quantum error correction and noise mitigation strategies.
- Mentor and guide a team of elite data scientists and quantum engineers.
- Collaborate with cross-functional teams to translate complex quantum research into market-ready products.
- Establish best practices for quantum software development and deployment pipelines.
- Present research findings and architectural blueprints to executive stakeholders and international conferences.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Physics, Mathematics, or a related field with a focus on Quantum Mechanics or Artificial Intelligence.
- Minimum of 7 years of professional experience in AI/ML engineering, with at least 3 years specifically in quantum computing or advanced simulation.
- Deep proficiency in programming languages such as Python, C++, and CUDA.
- Hands-on experience with quantum computing frameworks (e.g., Qiskit, Cirq, PyQuil) and cloud quantum platforms (e.g., IBM Quantum, AWS Braket).
- Proven track record of publishing peer-reviewed research in top-tier journals or conferences.
- Strong leadership skills with the ability to drive technical vision in a fast-paced, innovative environment.
- Experience with distributed systems and large-scale data processing (e.g., Spark, Hadoop).