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) required for deployable computational advantage over classical High-Performance Computing (HPC). Market constraints driven by system noise, decoherence management, and the need for energy efficiency necessitate dedicated performance oversight to ensure economic viability and scalability.
The role type is situated firmly within the Quantum Hardware segment of the value chain, specifically focusing on complex physical implementations like neutral atom platforms. Current industry maturation is severely constrained by the scalability bottleneck, where increasing qubit counts often introduces proportional increases in system complexity and noise. Performance engineering provides the crucial feedback loop required to mitigate this, moving systems beyond laboratory prototypes towards predictable, repeatable operation. The challenge of integrating heterogeneous sub-systems—including vacuum chambers, advanced laser control, and custom electronics—demands continuous, physics-informed optimization, a gap this specialization directly addresses. Furthermore, the global push toward sustainable computing places a premium on maximizing the computational output per watt, directly linking performance optimization to broader HPC energy efficiency metrics. Workforce and infrastructure development remain priority areas across the value chain, as multidisciplinary talent capable of bridging deep physics with industrial engineering standards is scarce. The continuous optimization of QPU metrics is foundational to attracting enterprise adoption, as institutional buyers demand reliable, benchmarked fidelity and throughput data before committing to quantum access infrastructure.
The capability architecture for this engineering function requires a seamless integration of experimental physics understanding, particularly concerning atom-light interaction dynamics, with rigorous systems engineering methodologies. Core tooling layers include high-level programming environments, primarily Python, leveraged for large-scale data acquisition, complex simulation of quantum dynamics, and the development of automated analysis pipelines. Expertise in formal version control systems (such as Git) is crucial for managing the rapid, iterative hardware and software release cycles endemic to deep-tech R&D. Furthermore, successful system performance validation depends on proficiency in developing and applying physics-based analytical models to predict hardware limitations, enabling optimization efforts to transition from empirical tuning to first-principles design iteration. This integrated skillset ensures predictable QPU uptime and the robust reproducibility of high-fidelity quantum operations across the deployed fleet. * Establishes standardized, reliable benchmarking metrics for QPU performance.
* Accelerates the commercial timeline for achieving useful quantum computational advantage.
* Reduces system gate error rates through precise, continuous physics-based calibration.
* Advances the Technology Readiness Level of complex neutral atom architectures.
* Supports the critical industrial transition to higher qubit counts and connectivity.
* Mitigates operational fidelity drift and environmental decoherence issues in hardware.
* Addresses the systemic challenge of integrating fragile quantum physics with robust engineering standards.
* Facilitates progress toward energy efficiency targets for next-generation quantum hardware.
* Improves empirical performance benchmarking necessary for enterprise adoption decisions.
* Shortens hardware development and iteration cycles via rapid diagnostic feedback.
* Enhances the deployment stability and long-term reliability of Quantum Processing Unit infrastructure.
* Drives the integration of advanced quantum control techniques validated by experimental data.Industry Tags: Quantum Computing Hardware, Neutral Atom Systems, Experimental Physics, Quantum System Engineering, Performance Optimization, QPU Validation, High-Performance Computing, Deep-Tech, Laser Engineering, System Integration.
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