Hypervision Surgical Ltd
HypervisionSurgical("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 clearancein 2025 under a newly established AI/ML productcode, andwas admitted into the FDA's Safer Technology Program. With multi-centre clinical evaluations underway and strategic partnershipswith world-leading technology and surgical manufactures,includingimecandZEISS Ventures,Hypervisionis 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. The Role 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. Key Responsibilities Optical & Spectral Characterisation 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. Acquisition Automation & Integration 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 internal tooling that lowers the friction of routine characterisation, calibration, maintenance, and verification work across the team. Calibration & Maintenance Cycle Take ownership of routine calibration, maintenance and quality control across deployed clinical systems, including management of calibration schedules, traceability to reference standards, and clear pass/fail records. Support the development and formalisation of calibration and maintenance procedures as the number of deployed systems grows. Investigate anomalies and perform root-cause analysis on imaging performance issues identified in the lab or in the field. Cross-Functional Collaboration Work closely with research scientists, system integration engineers, software developers, clinical application specialists and the clinical development team members to bring learnings from the bench into product and pipeline improvements. Translate findings from characterisation and testing into clear, actionable input for engineering and product decisions. Contribute to test documentation and evidence packages in support of verification, validation, and regulatory submissions. About You You are a hands-on, methodical engineer who enjoys working in the lab, assembling optics-based rigs and writing scripts that makes lab work repeatable. You are comfortable bridging hardware and software, enjoying wiring up instrumentation, scripting acquisition pipelines, and analysing the resulting data. You take pride in well-characterised systems, well-documented procedures, and measurements that other people can rely on, including in regulated contexts where the quality of your records matters as much as the quality of your data. You bring: BSc or MSc (with strong practical experience) in Physics, Optics, Biomedical Engineering, Electrical Engineering, or a related technical discipline Hands-on experience with optical imaging systems and optics-bench measurements, including spectral and transmission characterisation, gain and exposure characterisation, and resolution or image quality assessment. Experience working with image and video data, including basic processing, quality assessment, and debugging of imaging pipelines. Comfortable interacting with clinicians, customers, or external partners to diagnose issues and translate them into engineering improvements Proficiency in Python (or similar) for instrument control, benchtop automation, and data analysis using scientific libraries (NumPy, SciPy, Pandas); experience interfacing Python with hardware via vendor SDKs or standard protocols Comfortable bridging hardware and software - wiring up cameras, light sources, and motion control to scripted acquisition pipelines Strong attention to detail and a methodical, documentation-first approach to lab work Excellent oral and written communication skills Analytical thinker, attentive to details, creative and a team player Experience working with hyperspectral, multispectral, or other scientific imaging cameras, including spectral and per-band performance characterisation Experience working in a regulated industry, preferably MedTech, including familiarity with ISO 13485-compliant laboratory practice Experience working with liquid tissue phantoms, tissue-mimicking optical materials, or comparable experimental imaging targets Bonus points if you bring a special talent, interest, language, or unique life experience to the team. What We Offer The opportunity to make a direct contribution to patient care and deliver real-world surgical impact Access to state-of-the-art surgical development facilities at St Thomas' MedTech Hub, including hospitals, operating rooms, labs, and computational resources, with offices located at the London Institute for Healthcare Engineering Equity participation via share option scheme 25 days of annual leave plus bank holidays Hybrid working arrangements, tailored with your manager to suit the needs of the role Employee Assistance Programme for wellbeing, legal, and financial support Cycle to Work Scheme and Workplace Nursery Benefits £150 annual tech stipend for productivity and office essentials Complimentary office snacks and drinks Monthly team socials in an inclusive, collaborative culture
HypervisionSurgical("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 clearancein 2025 under a newly established AI/ML productcode, andwas admitted into the FDA's Safer Technology Program. With multi-centre clinical evaluations underway and strategic partnershipswith world-leading technology and surgical manufactures,includingimecandZEISS Ventures,Hypervisionis 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. The Role 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. Key Responsibilities Optical & Spectral Characterisation 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. Acquisition Automation & Integration 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 internal tooling that lowers the friction of routine characterisation, calibration, maintenance, and verification work across the team. Calibration & Maintenance Cycle Take ownership of routine calibration, maintenance and quality control across deployed clinical systems, including management of calibration schedules, traceability to reference standards, and clear pass/fail records. Support the development and formalisation of calibration and maintenance procedures as the number of deployed systems grows. Investigate anomalies and perform root-cause analysis on imaging performance issues identified in the lab or in the field. Cross-Functional Collaboration Work closely with research scientists, system integration engineers, software developers, clinical application specialists and the clinical development team members to bring learnings from the bench into product and pipeline improvements. Translate findings from characterisation and testing into clear, actionable input for engineering and product decisions. Contribute to test documentation and evidence packages in support of verification, validation, and regulatory submissions. About You You are a hands-on, methodical engineer who enjoys working in the lab, assembling optics-based rigs and writing scripts that makes lab work repeatable. You are comfortable bridging hardware and software, enjoying wiring up instrumentation, scripting acquisition pipelines, and analysing the resulting data. You take pride in well-characterised systems, well-documented procedures, and measurements that other people can rely on, including in regulated contexts where the quality of your records matters as much as the quality of your data. You bring: BSc or MSc (with strong practical experience) in Physics, Optics, Biomedical Engineering, Electrical Engineering, or a related technical discipline Hands-on experience with optical imaging systems and optics-bench measurements, including spectral and transmission characterisation, gain and exposure characterisation, and resolution or image quality assessment. Experience working with image and video data, including basic processing, quality assessment, and debugging of imaging pipelines. Comfortable interacting with clinicians, customers, or external partners to diagnose issues and translate them into engineering improvements Proficiency in Python (or similar) for instrument control, benchtop automation, and data analysis using scientific libraries (NumPy, SciPy, Pandas); experience interfacing Python with hardware via vendor SDKs or standard protocols Comfortable bridging hardware and software - wiring up cameras, light sources, and motion control to scripted acquisition pipelines Strong attention to detail and a methodical, documentation-first approach to lab work Excellent oral and written communication skills Analytical thinker, attentive to details, creative and a team player Experience working with hyperspectral, multispectral, or other scientific imaging cameras, including spectral and per-band performance characterisation Experience working in a regulated industry, preferably MedTech, including familiarity with ISO 13485-compliant laboratory practice Experience working with liquid tissue phantoms, tissue-mimicking optical materials, or comparable experimental imaging targets Bonus points if you bring a special talent, interest, language, or unique life experience to the team. What We Offer The opportunity to make a direct contribution to patient care and deliver real-world surgical impact Access to state-of-the-art surgical development facilities at St Thomas' MedTech Hub, including hospitals, operating rooms, labs, and computational resources, with offices located at the London Institute for Healthcare Engineering Equity participation via share option scheme 25 days of annual leave plus bank holidays Hybrid working arrangements, tailored with your manager to suit the needs of the role Employee Assistance Programme for wellbeing, legal, and financial support Cycle to Work Scheme and Workplace Nursery Benefits £150 annual tech stipend for productivity and office essentials Complimentary office snacks and drinks Monthly team socials in an inclusive, collaborative culture
Hypervision Surgical Ltd
HypervisionSurgical("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 clearancein 2025 under a newly established AI/ML productcode, andwas admitted into the FDA's Safer Technology Program. With multi-centre clinical evaluations underway and strategic partnershipswith world-leading technology and surgical manufactures,includingimecandZEISS Ventures,Hypervisionis 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. The role We are seeking an experienced Senior Machine Learning Engineer to support the development and deployment of our AI/ML surgical vision platform, taking algorithms from research prototype to production deployment, and building the data pipelines that turn our hyperspectral imaging system into a continuously improving clinical tool. As a Senior Machine Learning Engineer, you will work alongside our research scientists, engineers, and clinical development team to shape both the algorithms and the platform that delivers them. In particular, you will contribute architecturally and in a hands-on capacity to the design, training, evaluation, and production deployment of machine learning models for hyperspectral image processing, including image reconstruction, tissue characterisation, and semantic segmentation design and build the data pipelines that turn raw clinical recordings into structured, governed training datasets, supporting continuous training, model improvement, and re-validation cycles architect and operate the production ML stack, including model versioning, deployment, monitoring, drift detection, and rollback, for our cloud-enabled, regulatory-cleared surgical imaging platform establish and maintain MLOps best practices, including reproducible training, dataset governance, experiment tracking, model documentation, that scale across multiple algorithms, sensors, and clinical indications mentor more junior research scientists and engineers identify and surface novel features in support of patenting activities work closely with our software development and regulatory team for efficient integration from R&D to deployment At Hypervision Surgical, we welcome candidates who have the core skills for the post and are keen to learn and grow with us. We are committed to creating an inclusive environment where a diverse mix of talented people come and enjoy working with each other. By working together, we will change the way surgery is performed and improve patient care. A bitaboutyou PhD or MSc in Machine Learning, Physics, Mathematics, Computer Vision, or related technical discipline 6+ years industry experience designing, training, evaluating, and deploying machine learning models, ideally for vision applications in a regulated medical context Demonstrated track record of taking ML systems from research prototype to production deployment at scale Strong experience building and maintaining data pipelines for continuous training, with a focus on reproducibility, dataset versioning, and efficient access Working knowledge of cloud platforms (AWS, GCP, or Azure) and modern MLOps tooling (e.g. MLflow, Weights & Biases, DVC, Airflow) Strong experience with Python and associated scientific software packages such as PyTorch, OpenCV, Pandas, SciPy, NumPy, SciKit-learn, etc. Strong software engineering practices including version control, code review, software testing methodologies, and continuous integration; experience with IEC 62304 is particularly desirable Excellent oral and written communication skills, and comfort working at the interface between research, engineering, regulatory, and clinical teams Experience mentoring or leading junior engineers or scientists Analytical thinker, attentive to details, creative and team player Bonus points if you bring a special talent, interest, new language, or unique life experience to the team. What we offer The opportunity to make a direct contribution to patient care and deliver real-world surgical impact Access to state-of-the-art surgical development facilities at St Thomas' MedTech Hub, including hospitals, operating rooms, labs, and computational resources, with offices located at the London Institute for Healthcare Engineering Equity participation via share option scheme 25 days of annual leave plus bank holidays Hybrid working arrangements, tailored with your manager to suit the needs of the role Employee Assistance Programme for wellbeing, legal, and financial support Cycle to Work Scheme and Workplace Nursery Benefits £150 annual tech stipend for productivity and office essentials Complimentary office snacks and drinks Monthly team socials in an inclusive, collaborative culture
HypervisionSurgical("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 clearancein 2025 under a newly established AI/ML productcode, andwas admitted into the FDA's Safer Technology Program. With multi-centre clinical evaluations underway and strategic partnershipswith world-leading technology and surgical manufactures,includingimecandZEISS Ventures,Hypervisionis 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. The role We are seeking an experienced Senior Machine Learning Engineer to support the development and deployment of our AI/ML surgical vision platform, taking algorithms from research prototype to production deployment, and building the data pipelines that turn our hyperspectral imaging system into a continuously improving clinical tool. As a Senior Machine Learning Engineer, you will work alongside our research scientists, engineers, and clinical development team to shape both the algorithms and the platform that delivers them. In particular, you will contribute architecturally and in a hands-on capacity to the design, training, evaluation, and production deployment of machine learning models for hyperspectral image processing, including image reconstruction, tissue characterisation, and semantic segmentation design and build the data pipelines that turn raw clinical recordings into structured, governed training datasets, supporting continuous training, model improvement, and re-validation cycles architect and operate the production ML stack, including model versioning, deployment, monitoring, drift detection, and rollback, for our cloud-enabled, regulatory-cleared surgical imaging platform establish and maintain MLOps best practices, including reproducible training, dataset governance, experiment tracking, model documentation, that scale across multiple algorithms, sensors, and clinical indications mentor more junior research scientists and engineers identify and surface novel features in support of patenting activities work closely with our software development and regulatory team for efficient integration from R&D to deployment At Hypervision Surgical, we welcome candidates who have the core skills for the post and are keen to learn and grow with us. We are committed to creating an inclusive environment where a diverse mix of talented people come and enjoy working with each other. By working together, we will change the way surgery is performed and improve patient care. A bitaboutyou PhD or MSc in Machine Learning, Physics, Mathematics, Computer Vision, or related technical discipline 6+ years industry experience designing, training, evaluating, and deploying machine learning models, ideally for vision applications in a regulated medical context Demonstrated track record of taking ML systems from research prototype to production deployment at scale Strong experience building and maintaining data pipelines for continuous training, with a focus on reproducibility, dataset versioning, and efficient access Working knowledge of cloud platforms (AWS, GCP, or Azure) and modern MLOps tooling (e.g. MLflow, Weights & Biases, DVC, Airflow) Strong experience with Python and associated scientific software packages such as PyTorch, OpenCV, Pandas, SciPy, NumPy, SciKit-learn, etc. Strong software engineering practices including version control, code review, software testing methodologies, and continuous integration; experience with IEC 62304 is particularly desirable Excellent oral and written communication skills, and comfort working at the interface between research, engineering, regulatory, and clinical teams Experience mentoring or leading junior engineers or scientists Analytical thinker, attentive to details, creative and team player Bonus points if you bring a special talent, interest, new language, or unique life experience to the team. What we offer The opportunity to make a direct contribution to patient care and deliver real-world surgical impact Access to state-of-the-art surgical development facilities at St Thomas' MedTech Hub, including hospitals, operating rooms, labs, and computational resources, with offices located at the London Institute for Healthcare Engineering Equity participation via share option scheme 25 days of annual leave plus bank holidays Hybrid working arrangements, tailored with your manager to suit the needs of the role Employee Assistance Programme for wellbeing, legal, and financial support Cycle to Work Scheme and Workplace Nursery Benefits £150 annual tech stipend for productivity and office essentials Complimentary office snacks and drinks Monthly team socials in an inclusive, collaborative culture