Quantum Scientist - Community, AI & Learning Systems

About the role

QuEra Computing is seeking a mission-driven Quantum Scientist focused on designing and delivering specialized content for community engagement, customer training, and AI-enabled learning experiences. You'll use your expertise in quantum information, machine learning, and modern AI systems to create learning pathways that bridge users to the latest outcomes in quantum computing research - particularly that by QuEra's team - via our Bloqade software suite and our current and upcoming neutral-atom hardware. In addition to building world-class educational content, you will help integrate AI agents, ML-driven analytics, and scalable infrastructure into our enablement ecosystem-enhancing user onboarding, experimentation workflows, and community engagement. Deliverables include lessons, tutorials, notebooks, AI-assisted labs, hackathon challenges, interactive agents, and technical presentations tailored to users across academia, national labs, and industry. Some travel may be required for workshops, conferences, and hackathons.

Responsibilities

• Design, author, and maintain structured, hands-on learning materials (courses, tutorials, notebooks, problem sets, quizzes, and challenge tracks) aligned with neutral-atom quantum computing capabilities.
• Develop AI-enhanced learning tools, including intelligent tutoring workflows, agent-assisted coding labs, and automated feedback systems.
• Build and deploy lightweight ML or AI agent systems that support user onboarding, documentation navigation, experiment configuration, or workflow optimization.
• Produce clear, accurate technical presentations and demos for customers, partners, conferences, and hackathons; deliver live and online instruction.
• Closely collaborate with the applications research, product and solutions teams to ensure content reflects the latest algorithms, applications, APIs, and hardware constraints.
• Translate new R&D into learner pathways; define objectives and assessments; use learner data, ML-driven insights, and feedback to iterate and improve.
• Contribute to scalable infrastructure for educational environments (cloud-based notebooks, APIs, model endpoints, experiment orchestration systems).
• Drive customer/partner enablement and community programs (hackathons, forums, workshops) and expand documentation to lower adoption barriers.
• Explore and prototype AI agents that assist users in quantum program synthesis, parameter optimization, debugging, or workflow automation.

Requirements

• Advanced experience in Physics, Computer Science, Electrical Engineering, Machine Learning, or a related field (PhD preferred; MSc/BSc with equivalent experience considered).
• Strong foundation in quantum information/science, spanning algorithmic building blocks, software tooling, data analysis, and hardware limitations.
• Experience using machine learning systems, AI agents, LLM-based tooling, or intelligent automation frameworks.
• Familiarity with modern ML/AI infrastructure (e.g., model APIs, vector databases, agent orchestration frameworks, cloud deployment, experiment tracking).
• Experience creating technical education materials or teaching (tutorials, workshops, developer content), with demonstrated interest in research-informed pedagogy.
• Excellent written and verbal communication skills; ability to explain complex topics to diverse technical audiences.
• Collaborative mindset and the discipline to independently deliver high-quality technical and educational artifacts.
• Experience with Bloqade or other QIS tooling for scientific computing.
• Familiarity with neutral-atom quantum computing platforms.
• Experience applying ML techniques and agents to scientific and quantum computing, particularly in the context of education.
• Experience building or deploying AI agents (e.g., retrieval-augmented systems, code assistants, orchestration frameworks).
• Experience with MLOps, infrastructure-as-code, containerization, or cloud-based notebook environments.
• Track record presenting at conferences, running hackathons, or building developer communities.
• Comfort using data analytics and ML methods to evaluate learning outcomes and improve curricula.
• The approximate base salary range for this position is $130,400 - $211,900.

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