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Qblox is a deep-tech scaleup whose mission is to accelerate the worldwide race towards scalable quantum computers. We do this by providing some of the world's most advanced quantum control stacks to laboratories and quantum startups across the globe.
Our hardware and software sit right next to the quantum chips, giving experimentalists precise control and readout of their qubits. Through our open-source interfaces qblox-scheduler and qblox-instruments, users can write and execute experiments and algorithms using Python – from defining quantum circuits to compiling down to our quantum assembly, Q1ASM.
We offer a dynamic environment where engineering meets cutting-edge physics research.
About The Role
You will help build and evolve the software engine that drives the Qblox Cluster, our modular control platform capable of orchestrating 100+ qubit systems with nanosecond timing precision – and scaling towards 1,000+ and beyond.
You'll join a team of 7 software engineers with diverse nationalities and backgrounds. Together you'll make our compiler smarter and faster, continuously update logic to reflect new requirements, and open the software up for extensions and new features.
Your focus will be on designing and implementing features for advanced quantum experiments, and shaping the architecture of our control stack with an emphasis on scalability, performance, and clean abstractions.
Note: a physics or quantum computing background is nice to have, but not required in our day-to-day job.
What You Will Do
- Design and ship new features: Extend qblox-scheduler and qblox-instruments so experimentalists can run more complex experiments and iterate faster on their research.
- Improve the compiler: Optimize instruction scheduling, register allocation, and control flow for our distributed Q1 Sequence Processors. We currently support 100+ qubits and want to move towards 1,000+ and eventually 10,000+.
- Shape the architecture: Contribute to the architectural design of our software stack, ensuring scalability, maintainability, and performance optimization.
- Support reproducible quantum experiments: Help ensure experiments are predictable and repeatable by tightening the loop between software, firmware, and hardware.
- Integrate with advanced control hardware: Collaborate with hardware and firmware engineers to expose new hardware capabilities via robust APIs, drivers, and abstractions that users can rely on.
- Quality assurance and collaboration: Participate in code reviews, testing, and debugging. Actively improve team processes and software quality.
Python (advanced), Q1ASM (Qblox's quantum assembly), qblox-scheduler, qblox-instruments, Git, and modern CI/CD tools.
Enough about us, what about you?
In order to really enjoy the role with us, we anticipate that you will have a background encompassing the following:
- Experience: 4+ years of professional software engineering experience, preferably on backend systems, drivers, compilers, or embedded/toolchain-like software.
- Python proficiency: You are fluent in Python and comfortable working in a non-trivial codebase, with a strong understanding of object-oriented programming principles (e.g., SOLID principles and design patterns).
- Engineering rigor: You care about clean APIs, clear contracts, and good software engineering principles.
- Scalability & performance mindset: You have worked on systems where latency, throughput, or resource usage matter, and you can articulate trade-offs.
- Collaboration: Ability to work effectively in an international, English-speaking environment.
- Tooling: Experience with version control systems such as Git and familiarity with CI/CD practices and tools.
- Compiler expertise: Background in compiler design, ASTs, intermediate representations (IRs), or transpilers. Familiarity with LLVM or MLIR.
- Hard engineering: Experience with real-time constraints, Digital Signal Processing, or FPGA-based architectures.
- System-level languages: Experience with C++, Rust, or similar.
- Scientific/quantum software: Experience with quantum or scientific Python software such as Qiskit, Q-CTRL, QUA, Cirq, CUDA-Q, QCoDeS, NumPy, SciPy, xarray, pytest, etc.
- Physics background: Knowledge of physics, particularly quantum mechanics or quantum computing concepts.
- Open source & agile: Experience contributing to open-source projects or working in agile, cross-functional teams.
Key Skills
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