A propos de Pasqal
Pasqal conçoit et développe des processeurs quantiques (QPUs : Quantum Processing Units) et les outils logiciels associés.
Notre technologie innovante permet de traiter des cas d’usage qui sont à ce jour hors de portée des plus puissants des supercalculateurs ; ces cas peuvent concerner des défis industriels applicatifs aussi bien que les besoins des sciences fondamentales.
Au-delà de la puissance de calcul exceptionnelle qu’ils apportent, les QPUs sont d’une très grande efficacité énergétique et contribueront à réduire fortement l’empreinte carbone de l’industrie du calcul intensif.
Job Description
Vous souhaitez relever un défi stimulant au cœur des technologies de pointe? Vous aimeriez contribuer au développement de dispositifs servant au contrôle d’ordinateurs quantiques? Joignez-vous à l’équipe innovante d’Aeponyx!
Nous recherchons un scientifique ou un ingénieur spécialisé en automatisation et en gestion de données. La personne retenue travaillera en étroite collaboration avec l’équipe de développement des tests et l’équipe du laboratoire afin de concevoir, mettre en œuvre et automatiser l’infrastructure de gestion des flux de données.
Responsabilités
- Concevoir, programmer et maintenir la couche logicielle d’acquisition de données pour les activités du laboratoire et des essais.
- Concevoir, programmer et maintenir l’infrastructure de stockage ainsi que les systèmes de gestion des bases de données.
- Collaborer avec les partenaires d’assemblage, de conditionnement et avec d’autres fournisseurs afin d’harmoniser les données d’essai ou de caractérisation liées aux pièces et aux assemblages externalisés.
- En collaboration avec d’autres ressources internes, spécifier, acquérir et déployer l’architecture informatique requise pour soutenir les différents systèmes de gestion des données mentionnés ci-dessus.
Profil recherché
- Compétences en programmation (Python, C#).
- Expérience en automatisation d’outils de fabrication et en transfert de données.
- Expérience en conception et en gestion de bases de données.
Formation:
- Diplôme en génie logiciel, en génie électrique, en génie physique ou en génie informatique, ou tout autres domaines d’étude pertinent lié à la science ou à l’analyse de données scientifiques.
Atouts:
- Connaissance de la microfabrication ou de la microélectronique.
- Expérience en caractérisation de systèmes optiques
- Expérience en suivi de production dans un système d’assurance qualité.
- Expérience concrète du travail en équipe et grande autonomie dans l’exécution des tâches.
Langue:
La personne retenue doit être en mesure de communiquer efficacement en français, tant à l’oral qu’à l’écrit. La connaissance de l’anglais constitue un atout pour collaborer avec d’autres scientifiques possédant une expertise particulière, ainsi qu’avec des partenaires situés à l’extérieur du pays.
Conditions
- Temps plein, permanent
- Vacances : À partir de 4 semaines par année
- Salaire : 70 000$ - 90 000$ (fourchette selon l'expérience et formation)
À propos d’Aeponyx
Basée à Montréal, Aeponyx (www.aeponyx.com) est un leader dans le développement de dispositifs de photoniques intégrés en nitrure de silicium. Grâce à sa technologie brevetée qui allie les systèmes micro électromécaniques (MEMS) et la photonique sur silicium, nous concevons et fabriquons des circuits de photonique intégrée (PIC) destinés aux applications de télécommunications, aux centres de données et aux technologies quantiques. Aeponyx est une filiale canadienne de Pasqal SAS (https://www.pasqal.com/fr/), pionner mondial des ordinateurs quantiques à atomes neutres.
Pasqal est un employeur garantissant l'égalité des chances. Nous nous engageons à créer un lieu de travail diversifié et inclusif, car l'inclusion et la diversité sont essentielles à la réalisation de notre mission. Nous encourageons les candidatures de tous les candidats qualifiés, quels que soient leur sexe, leur race, leur origine ethnique, leur âge, leur religion ou leur orientation sexuelle
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Pasqal designs and develops Quantum Processing Units and dedicated software tools. These innovative processors address applications which are out of the reach of the most powerful existing supercomputers, encompassing real-world challenges as well as fundamental science. As they are very low energy intensive, they will significantly contribute to reduce the carbon footprint of the computing industry.
Pasqal has partnerships with key users in the fields of energy, IT, finance, drug and chemical design, automotive. The maturity and potential of our technology and the quality of our scientific team has been rewarded several times at French, European and global levels.
Job Description
Are you looking for an exciting challenge at the heart of cutting-edge technologies? Would you like to contribute to the development of devices that control quantum computers? Join Aeponyx’s innovative team!
We are looking a Scientist or Engineer specializing in Automation and Data Management. The successful candidate will work in close collaboration with the test development team and the laboratory team to design, implement, and automate the data workflow infrastructure.
Main responsibilities :
- Design, program, and maintain the software layer for data acquisition across laboratory and testing activities.
- Design, program, and maintain the storage infrastructure as well as database management systems.
- Collaborate with assembly, packaging, and other external suppliers to standardize test and characterization data related to outsourced components and assemblies.
- Working with internal resources, specify, acquire, and deploy the IT architecture required to support the various data management systems mentioned above.
Candidate Profile
Technical Requirements
- Programming Skills: Proficiency in Python and C#.
- Automation: Experience in manufacturing tool automation and data transfer.
- Database Management: Experience in database design and management.
Education
- Degree in Software Engineering, Electrical Engineering, Engineering Physics, Computer Engineering, or any other relevant field of study related to data science or scientific data analysis.
Nice-to-Have Assets
- Knowledge of microfabrication or microelectronics.
- Experience in the characterization of optical systems.
- Experience in production tracking within a quality assurance system.
- Proven teamwork experience coupled with a high degree of autonomy in executing tasks.
Language Skills
- The successful candidate must be able to communicate effectively in French, both spoken and written. Knowledge of English is considered an asset for collaborating with specialized international scientists and global partners.
Right to work in Canada without sponsorship is preferred.
About Aeponyx
Based in Montreal, Aeponyx (www.aeponyx.com) is a leader in the development of integrated photonic devices in silicon nitride. Thanks to its patented technology combining micro-electromechanical systems (MEMS) with silicon photonics, we design and manufacture integrated photonic circuits (PICs) for telecommunications, data centers, and quantum technology applications. Aeponyx is a Canadian subsidiary of Pasqal SAS (https://www.pasqal.com/fr/), a global pioneer in neutral-atom quantum computers
TECHNICAL & MARKET ANALYSIS | Appended by Quantum.Jobs
The transition of quantum computing from laboratory proof-of-concept to industrial utility-scale deployment necessitates a robust software-hardware interface capable of managing complex data lifecycles. This role type is structurally essential for bridging the gap between quantum hardware fabrication and the high-throughput data environments required for reliable system characterization. By automating the extraction and management of performance metrics from integrated photonic circuits, this function ensures the deterministic scaling of neutral-atom and photonic quantum processors. Market signals from the QED-C and national technology strategies emphasize that such data-centric engineering is critical for mitigating the systemic risks associated with hardware variability and low yield in deep-tech supply chains. Consequently, this role acts as a primary stabilizer within the quantum enablement layer, facilitating the transition toward fault-tolerant architectures and sustainable industrial production.
The quantum technology ecosystem is currently navigating a decisive shift from lab-scale experimentation to industrial-scale manufacturing. As hardware modalities such as neutral atoms and integrated photonics mature, the primary bottleneck has transitioned from basic qubit coherence to the reproducibility and scalability of the entire system. This evolution requires a sophisticated infrastructure for data acquisition and process control that can handle the massive parallelism of modern quantum processors. Current industry focus lies on bridging classical and quantum capabilities at scale, necessitating the integration of specialized software layers that can orchestrate complex testing protocols across fragmented global supply chains.
Workforce scarcity remains acute for individuals capable of synchronizing semiconductor-grade microfabrication data with high-level software automation. In the Montreal quantum hub and other global centers, the lack of standardized benchmarking protocols for photonic components creates a high-risk dependency for organizations moving toward commercial readiness. This structural layer of expertise is the primary mechanism for maintaining momentum as technologies transition through varying Technology Readiness Levels (TRLs). Without rigorous, automated data management, the feedback loops between hardware testing and design iteration remain too slow to meet the aggressive roadmaps of the global quantum race.
Furthermore, the integration of quantum systems into existing high-performance computing (HPC) environments depends on the stability of the underlying control and monitoring software. The evolution of the value chain relies on the ability to translate raw physical signals into actionable engineering insights without disrupting established quality assurance frameworks. Ongoing ecosystem initiatives aim to accelerate readiness for practical quantum applications by focusing on the interoperability of hardware control layers. This systemic requirement places a premium on roles that can drive the convergence of data science, automation, and quantum information science within a unified production environment.
The capability architecture for this role type centers on the synchronization of low-level data acquisition with enterprise-grade database infrastructure. Mastery of the software layer is essential for ensuring that hardware characterization is optimized for the specific constraints of quantum processors, such as high-fidelity gate operations and optical system stability. This requires a deep understanding of the interface points between diverse programming environments and the underlying hardware drivers that manage real-time data flows. These capabilities are fundamental to the throughput of technology organizations like Pasqal, as they enable the parallelization of hardware development alongside the deployment of scalable testing frameworks.
By establishing rigorous verification and validation architectures, this function provides the leverage needed to assess the true performance of quantum components before full-scale integration. Furthermore, the ability to manage complex data schemas ensures that scientific outputs are reconciled with the practical constraints of industrial quality control and outsourced assembly. Such expertise reduces the iteration friction between fundamental physics breakthroughs and the delivery of scalable products, which is critical for long-term interoperability within the emerging quantum-as-a-service market. The role serves as the nexus between the physical qubit and the digital twin, ensuring data integrity across the entire technology stack. - Accelerates the deterministic transition from laboratory hardware testing to industrial-grade quantum processor production
- Mitigates systemic manufacturing risks by implementing automated data acquisition for integrated photonic components
- Facilitates the integration of hardware performance metrics into standardized high-performance computing monitoring systems
- Strengthens the reliability of quantum hardware roadmaps through the deployment of rigorous database architectures
- Reduces iteration friction between microfabrication teams and software developers via harmonized data flux management
- Optimizes the throughput of characterization labs by automating the feedback loops for optical system testing
- Enhances the stability of the quantum supply chain by standardizing data exchange with external packaging partners
- Supports the scaling of neutral-atom systems by managing the complex dependencies of control and automation software
- Improves the transparency of technology readiness level progression through deterministic performance benchmarking
- Enables the structural reproducibility of hardware tests across diverse geographical and organizational locations
- Protects high-capital research and development investments by ensuring data integrity throughout the hardware lifecycle
- Orchestrates the convergence of microelectronics protocols with the practical demands of universal quantum computingIndustry Tags: Integrated Photonics, Quantum Computing, Automation Engineering, Data Management, Silicon Nitride, Neutral-Atom QPUs, Microfabrication, Quality Assurance, Deep Tech Infrastructure
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