About Pasqal
PASQAL designs and develops Quantum Processing Units (QPUs) and associated software tools.
Our innovative technology enables us to address use cases that are currently beyond the reach of the most powerful supercomputers; these cases can concern industrial application challenges as well as fundamental science needs.
In addition to the exceptional computing power they provide, QPUs are highly energy efficient and will contribute to a significant reduction in the carbon footprint of the HPC industry.
Job Description
Pasqal's ambition is building and developing Quantum Processing Units (QPU) enabling highly performant computation using neutral atoms manipulated with lasers. On the hardware level, the complexity of the setup makes this journey unique and interesting. In the system performance team, we measure and optimize the performances of the QPU. We are responsible for the implementation and validation of new features and to push the system at its higher level of performances.
As a System Performance Engineer, your main responsibilities will be:
- Contribute to QPU wide projects
- Analyze performances (by developing simple mathematical and physics models and simulations) on current design and identify main limitations
- Propose new design or new techniques (hardware/software)
- Propose and perform documented system and sub-system tests plans to validate performance increase or new feature
- Contribute to maintaining dev QPUs in operation
- Propose new ideas leading to industrial innovation
- Collaborate closely with other teams in the hardware department
- Support the Manufacturing & Support team
- Communicate scientific results within and outside the team
- Supervise junior engineers and master students
To be successful in this role, you will have the following:
Requirements:
• M2 in physics +2/3 years in industry or PhD
• Knowledge in experimental physics (atom-light interaction physics would be appreciated)
• Strong interest in experimental physics and physics models
• Programming skills for data analysis and simulations (Python, ... )
• Versioning control is a plus (git tools)
• Experience in managing small-scale projects
Soft Skills:
- Autonomy, rigor and organization
- Communication and listening skills
- Proven ability to collaborate with multi-disciplinary teams (Theory, Experimental)
- Good level of written and spoken English. French is a plus but not required
What we offer
- Beautiful brand new offices in Massy, France
- Type of contract : CDI
- A dynamic and close-knit international team
- A key role in a growing start-up
Recruitment process
- An interview with our Talent Acquisition Specialist of 30'.
- An exchange with the Engineering manager of the team for 60 min.
- An onsite interview with the team in our offices.
- An offer!
PASQAL is an equal opportunity employer. We are committed to creating a diverse and inclusive workplace, as inclusion and diversity are essential to achieving our mission. We encourage applications from all qualified candidates, regardless of gender, ethnicity, age, religion or sexual orientation.
TECHNICAL & MARKET ANALYSIS | Appended by Quantum.Jobs
The Quantum System Performance Engineer function is structurally essential for de-risking the industrial transition of nascent quantum hardware. This role exists at the critical nexus of experimental physics and commercial engineering maturity, translating fragile physical phenomena into robust, benchmarked system architectures. Its primary impact lies in quantifying, modeling, and optimizing the operational fidelity and coherence metrics of Quantum Processing Units (QPUs), thereby accelerating the Technology Readiness Level (TRL) progression required for enterprise deployment. The scarcity of personnel capable of bridging deep atomic physics knowledge with scalable systems engineering methodologies makes this a high-leverage role in the current quantum workforce landscape. This performance validation loop is foundational to establishing commercial predictability and maximizing energy efficiency in high-performance computing (HPC) environments.
The system performance engineering function is positioned at the critical interface between QPU fabrication, experimental control systems, and the application layer. This placement is vital for mitigating the macro constraints currently challenging the quantum computing sector, particularly the scalability bottleneck and the Technology Readiness Level (TRL) mismatch between academic research and commercial deployment. Neutral-atom quantum computing, as employed by companies like Pasqal, necessitates exceptionally high standards of calibration and stability across complex laser and vacuum infrastructures. Fragmentation in the quantum hardware vendor landscape often means performance validation protocols must be custom-engineered, creating a demand for specialized engineering talent that possesses deep domain expertise in atomic physics alongside practical systems integration capabilities. Ongoing ecosystem initiatives aim to accelerate readiness for practical quantum applications, requiring persistent validation of operational stability under varying workloads, a core function of this role type. Establishing verifiable performance benchmarks (e.g., gate fidelity, qubit number, coherence time) is crucial for attracting both public sector funding and private enterprise adoption, shifting the technology from proof-of-concept to verifiable utility. This expertise directly supports the broader industry goal of bridging the gap between current Noisy Intermediate-Scale Quantum (NISQ) devices and future fault-tolerant architectures.
The technical architecture underpinning this role requires mastery of metrology protocols and low-level control systems. Core capabilities span statistical physics modeling for noise characterization, high-throughput data acquisition from experimental setups, and inverse problem solving to map empirical performance limitations back to specific hardware subsystems (e.g., laser stability, vacuum fluctuations). Proficiency in scientific programming environments, particularly Python for data processing, is standard for automating complex calibration routines and generating predictive system performance models. The role demands fluent interaction with quantum control layers, often involving pulse-shaping techniques, and knowledge of version control systems to maintain configuration integrity across highly sensitive hardware iterations. This skill convergence is necessary for rapid iteration cycles, transitioning experimental results into validated, scalable engineering specifications. Specialized knowledge in atom-light interaction physics provides the necessary theoretical grounding to diagnose and compensate for physical decoherence mechanisms at the fundamental level, ensuring that system performance metrics reflect genuine computational capacity. * Establishes quantifiable performance baselines for QPU architectures, supporting investor and enterprise due diligence.
* De-risks product roadmap execution by translating fundamental physics limitations into engineered solutions.
* Accelerates the industrialization path for quantum processors by standardizing test and validation methodologies.
* Contributes to reducing operational friction at the hardware-software interface layer.
* Optimizes resource allocation across engineering and research departments through empirical performance feedback.
* Drives the convergence of scientific discovery and scalable manufacturing processes.
* Minimizes the cost of hardware iteration by accurately modeling performance dependencies.
* Increases system uptime and predictability, critical for cloud-based quantum service delivery models.
* Benchmarks QPU capabilities against international standards, enhancing global competitiveness.
* Reduces energy consumption per computation by optimizing hardware control efficiency.
* Facilitates the smooth transition of experimental prototypes into commercial-grade systems.
* Provides the authoritative data required for comparative analysis against competing modalities.Industry Tags: Quantum Hardware Engineering, Neutral-Atom Computing, Experimental Quantum Physics, Qubit Performance Metrology, System Benchmarking, Ultra-High Vacuum Systems, Laser Control Systems, Quantum Processing Unit (QPU)
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