Imaging Systems Engineer

Hypervision Surgical(“Hypervision”)is a spin-out from King’s College London, founded by clinicians and experts in medical imaging and artificial intelligence. Using safe light alone, our mission is to equip surgeons with real-time, AI-driven tissue intelligence to improve precision and patient safety.

We are pioneering the world’s first regulatory-cleared real-time intraoperative spectral imaging platform, combining on-chip spectral sensing with high-speed AI analytics at over 60 frames per second. Seamlessly integrating into existing surgical vision systems, our technology transforms standard cameras into intelligent, data-rich tools, revealing anatomical, physiological, and pathological information beyond human vision.

Certified for both open and minimally invasive surgery, our platform achievedUKCA certificationandFDA clearance in 2025 under a newly established AI/ML product code, andwas admitted into the FDA’s Safer Technology Program. With multi-centre clinical evaluations underway and strategic partnerships with world-leading technology and surgical manufactures,includingimecandZEISS Ventures,Hypervision is shaping the future of data-driven surgery.

Hypervision Surgical process all personal data in accordance with the UK GDPR and Data Protection Act 2018. For further information on how we collect, use and protect your data, please refer to our Applicant Privacy Notice.

We are seeking a curious, hands-on and motivated individual to join us as our Imaging Systems Engineer
, to play a key role in the development, validation, and deployment of our surgical vision platform, spanning benchtop experimentation, data acquisition, system validation, and real-world system support.

In this role, you will work at the intersection of optical imaging, instrumentation, and scientific software, supporting system validation and ensuring that our cameras, scopes, and accessories are characterised, calibrated, and validated to the standards required for surgical use. You will contribute to the design and execution of experiments for system-level characterisation, alongside the acquisition of high-quality reference datasets to support algorithm development and performance benchmarking.

A particular focus of your work will be characterising the spectral performance and image quality of our surgical vision system. In addition, you will help translate benchtop performance into real-world settings by supporting system deployment, troubleshooting, and technical interactions with clinical and external partners.

Working closely with our research scientists and system integration engineers, you will plan and execute benchtop experiments
, build the automation that makes those experiments robust and repeatable
, and produce the analyses that turn raw measurements into actionable engineering decisions.

Your work will be foundational to the reliability and performance of our intraoperative imaging platform, supporting both ongoing maintenance of deployed clinical systems and the development of next-generation hardware
. You will contribute to the technical records and performance baselines that underpin our regulatory submissions and post-market surveillance activities.

• Plan, set up, and execute optical and imaging benchtop tests for new camera platforms, light sources, scopes, and accessories.
• Collect optical and spectral performance data and produce the analyses to interpret them, referencing defined performance metrics and acceptance criteria.
• Maintain accurate and up-to-date technical documentation of benchtop procedures, characterisation results, and component performance baselines, to the standard required for regulatory submissions.

• Design and implement automated data-acquisition routines in Python (or similar) for repeatable benchtop and integration testing, including scripted control of cameras, light sources, motion stages, and spectrometers via their respective hardware interfaces and SDKs.
• Develop and maintain scripts that link multiple instruments into reproducible, well-documented measurement workflows.
• Contribute to…