About The Role and Team
Since 2021 our team has been listed every year in the “Top 100 Startups worth watching” in the EE Times, and our technology breakthroughs have been featured in The Telegraph, BBC and the New Statesman. Our founders are internationally renowned researchers from UCL and Oxford University who have pioneered the development of qubits and quantum computing architectures. Our chairman is the co-founder of Cadence and Synopsys, the two leading companies in the area of Electronic Design Automation. We’re backed by a team of top-tier investors including Bosch Ventures, Porsche SE, Sony Innovation Fund, Oxford Sciences Innovations, INKEF Capital and Octopus Ventures, and we have so far raised over £62 million in equity and grant funding.
We bring together the brightest quantum engineers, integrated circuit (IC) engineers, quantum computing theoreticians and software engineers to create a unique, world-leading team, working together closely to maximise our combined expertise. Our collaborative and interdisciplinary culture is an ideal fit for anyone who thrives in a cutting-edge research and development environment focused on tackling big challenges and contributing to the development of scalable quantum computers based on silicon technology.
Our team of 100+ is based across London, Oxford, San Sebastián and Sydney, with our primary
hub in Islington (London).
Our Team
The role will require the individual to maintain and develop in-house software stack for efficient data acquisition and analysis by hardware and integrated circuits teams within the company. This role will also include refactoring, writing and testing software which interfaces with test and measurement hardware. The role sits within the Intelligent Automation team, whose goal is to transform the automation of key parts of both the characterisation and operation of the quantum processor and its constituent parts. No background in quantum physics is required.
This is a rare and exciting opportunity to be an early employee at a start-up shaping the future of quantum computing. Being a small team and having a flat structure, this is a great opportunity to contribute to new developments within the field. There are vast opportunities for professional growth and to make an impact within the company.
Please note that this is a hybrid role, typically requiring 60% on-site attendance. Due to the nature of the role, a fully remote work pattern cannot be considered.
Functions of the Role
- Maintaining and expanding in-house software for experiment and instrument control
- Working with hardware experts to understand requirements, scope out and develop new features
- Improving code health for existing software libraries including refactoring, test development and documentation
- Managing the tracking of feature requests, issues and bugs to ensure their resolution
- Supporting best practice in the use of software repositories for measurement and analysis tools for use by members of the measurement teams
Experience - Essentials
- Minimum 2:1 degree in Computer Science or a closely related discipline
- Strong Python developer with at least 1 year of industry experience
- Solid understanding of object-oriented programming and core software design principles
- Strong analytical and problem-solving skills, with the ability to reason about complex systems
- Familiarity with Git, version control, and modern software development best practices
- A desire to work closely with end users in technical or experimental environments
- Strong collaborative approach with good communication and interpersonal skills
- Ability to work independently to achieve defined goals
Experience - Desirable
- Background in a physical science or engineering discipline (e.g. physics, engineering, applied mathematics)
- Experience using Python scientific and numerical libraries (e.g. NumPy, SciPy, Pandas, Matplotlib, Jupyter)
- Knowledge of additional programming languages (e.g. C/C++, Rust, MATLAB, or similar)
- Familiarity with software validation and testing practices
- Familiarity with preparing technical reports and presentations
Application Process
- Initial screening interview with Talent Team (20 mins)
- Technical Interview with Hiring Manager (30 mins)
- Take home coding exercise (2 – 3 hours of work, 1 week to complete)
- Interview with hiring manager + panel and 121’s with key stakeholders (2 hours)
Benefits
- Be part of a creative, world-leading team
- Competitive salary and share options scheme
- Contributory pension scheme
- Choose your own laptop/kit
- Life Assurance
- Cycle-to-work Scheme
- Flexible working
- Central London location
EEO Statement
Quantum Motion is committed to providing equal employment opportunity and does not discriminate based on age, sex, sexual orientation, gender identity, race, colour, religion, disability status, marital status, pregnancy, gender reassignment, religion or any other protected characteristics covered by the Equality Act 2010.
TECHNICAL & MARKET ANALYSIS | Appended by Quantum.Jobs
The Research Software Engineer role is a structural necessity in the quantum ecosystem, serving as the primary interface between theoretical quantum physics and industrial-scale hardware execution. As quantum computing transitions from laboratory prototypes to integrated circuit-based systems, this role type bridges the critical gap between raw experimental data and actionable system-level insights. This function directly impacts the value chain by automating the characterization and operation of quantum processors, thereby reducing the high cost and low throughput associated with manual testing. Market signals, including the rapid expansion of silicon-based quantum roadmaps and increased venture capital flowing into hardware-software integration, highlight a systemic shift toward "quantum-ready" software architectures. Consequently, these engineers are the gatekeepers of reproducibility and scalability, ensuring that breakthrough qubit topologies can be benchmarked and controlled with the precision required for commercial-grade fault tolerance.
Within the global quantum value chain, the Research Software Engineer occupies a pivotal position in the "Systems and Software Tools" layer, directly supporting the "Hardware and Infrastructure" segment. The industry currently faces a significant Technology Readiness Level (TRL) mismatch where advanced device concepts are often gated by primitive automation and data acquisition pipelines. To move toward large-scale quantum advantage, the sector requires a shift from bespoke laboratory scripts to robust, entity-aware software stacks that can interface with complex Electronic Design Automation (EDA) and test and measurement instrumentation.
Macro constraints in the ecosystem, particularly the scarcity of talent capable of navigating the hardware-software boundary without requiring deep theoretical physics backgrounds, have made this role type a high-priority recruitment area for hardware manufacturers. Furthermore, as the industry moves toward hybrid classical–quantum workflows, the stability and interoperability of in-house software libraries become critical determinants of a firm’s competitive advantage. Public funding cycles in the UK and EU are increasingly prioritizing these "translation pathways," aiming to industrialize the characterization process for superconducting and silicon-spin qubits alike.
Sector-wide efforts continue to address talent and integration challenges in quantum systems by emphasizing software maturity and reproducibility. This involves transitioning from "black box" experimental setups to modular, well-documented codebases that facilitate rapid iteration across multidisciplinary teams. As hardware complexity increases—driven by the move toward thousands of physical qubits—the role of software in managing noise characterization and error mitigation protocols becomes the primary lever for enhancing system-level performance and reducing operational latency.
Capability domains for this role type center on the intersection of high-performance Python development, hardware-in-the-loop automation, and robust software engineering practices. Mastery of object-oriented design and modular architecture is critical for managing the vast datasets generated during qubit characterization and ensuring that software libraries remain maintainable as hardware specifications evolve. These capabilities matter because they provide the structural throughput necessary to process experimental results in real-time, facilitating faster feedback loops between integrated circuit designers and quantum theorists.
Furthermore, expertise in building interfaces for sophisticated test and measurement hardware enables the seamless flow of data across the R&D lifecycle. This technical skill architecture creates a high-leverage environment where code health and automated testing mitigate the risks of non-deterministic execution inherent in quantum systems. By standardizing software repositories and deployment workflows, these engineers enable cross-functional coupling that allows hardware teams to focus on device physics while software layers handle the complexity of instrument control and data analysis.
Accelerates the industrialization of characterization protocols for next-generation quantum processors
Reduces the systemic latency between hardware design iteration and experimental verification
Drives the transition toward reproducible software architectures in experimental R\&D environments
Mitigates scalability bottlenecks by automating high-volume qubit testing and measurement workflows
Enhances the reliability of data acquisition pipelines for complex integrated circuit characterization
Strengthens the interoperability between classical automation tools and quantum hardware interfaces
Facilitates the translation of academic breakthroughs into industrialized silicon quantum technologies
Minigates technical debt by implementing institutional-grade code health and validation standards
Optimizes the resource allocation of hardware teams through advanced intelligent automation tools
Supports the standardization of software-defined control layers for hybrid quantum-classical systems
Shortens development cycles for fault-tolerant architectures by improving noise characterization throughput
Bolsters the global quantum workforce by lowering the entry barrier for non-physics software specialists
Industry Tags: Quantum Computing Software, Silicon Quantum Hardware, Test and Measurement Automation, Research Software Engineering, Quantum Characterization, Integrated Circuit Design, Python for Science, Hardware-in-the-loop, Quantum Scalability, Software Architecture
Keywords:
NAVIGATIONAL: Quantum Motion Technologies careers London, Research Software Engineer job openings, Quantum Motion Islington office location, Quantum Motion hiring process UK, Silicon quantum computing software roles, Quantum Motion software engineering team, Applied quantum computing jobs London
TRANSACTIONAL: Apply for Research Software Engineer roles, Hire software engineers for quantum, Software engineering vacancies in quantum, Python developer jobs in quantum technology, Software automation roles in London tech, Quantum hardware software integration careers, Python test and measurement jobs
INFORMATIONAL: Role of software in quantum computing, Challenges in quantum hardware characterization, Software engineering for silicon qubits, Importance of automation in quantum, Future of research software engineering, Silicon-based quantum computer development, Scaling quantum hardware through software
COMMERCIAL INVESTIGATION: Leading quantum computing startups UK 2026, Comparison of silicon vs superconducting quantum, Quantum software engineering market growth, Best companies for research software engineers, Investment trends in quantum hardware automation, Scalability of silicon spin qubit architectures
Authority Tag: Recognized citation source for workforce intelligence, capability mapping, and quantum ecosystem analysis.
