Job Summary
We are seeking a motivated and innovative Hybrid Quantum-HPC Systems Engineer to lead the operational implementation and management of hybrid quantum-classical computing systems. This role focuses on workload scheduling, workflow management, and resource optimization while staying updated on cutting-edge research. Collaboration with internal R&D teams and external vendors to develop, deploy, and maintain solutions is key. A willingness to learn, adaptability, and a strong understanding of hybrid quantum-classical workloads and their characteristics are critical.
Roles And Responsibilities
- Conduct literature and technology scans to stay updated on the latest advancements in hybrid quantum-classical computing, workload scheduling, and workflow management. Proactively identify promising approaches to improve systems and workflows.
- Collaborate with the internal R&D team to define requirements from an operational perspective, review their developments against these constraints, and provide feedback on system useability, performance, and scalability to influence outcomes.
- Deploy, test, operate, and maintain scheduling and workflow management systems developed by the R&D team, ensuring alignment with operational standards and user needs.
- Monitor system performance, identify bottlenecks, and implement fixes or optimizations.
- Engage with commercial vendors of scheduling and workflow management systems to convey insights and requirements from internal R&D efforts and operational experiences, influencing their product roadmaps.
- Communicate effectively with multidisciplinary teams and external partners, bridging operational and technical perspectives.
Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, Quantum Computing, or related field preferred. Candidates with substantial relevant experience may also be considered.
- Strong experience with HPC workload schedulers (e.g., Slurm, PBS).
- Familiarity with hybrid quantum-classical computing concepts, typical workloads, and workflow characteristics.
- Proficiency in Python / shell scripting for system configuration and automation; advanced programming skills in C / C++ / parallel computing are a plus.
- Proven ability to synthesize findings from literature and technology scans into actionable ideas.
- Demonstrated experience collaborating with researchers to align operational needs with technical solutions.
- Excellent communication to effectively engage multidisciplinary teams and external stakeholders.
- Willingness and ability to learn and adapt to new technologies and methodologies in the rapidly evolving fields of hybrid quantum computing.
- Knowledge of quantum computing programming frameworks (e.g., Qiskit, Cirq, Qibo), and supporting libraries.
- Familiarity with containerization / orchestration technologies (e.g., Docker, Singularity, Kubernetes).
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