Medical Robot Autonomy Engineer

King's College London - Surgical & Interventional Engineering

About us:

We are seeking a software engineer with core expertise in computer vision and machine learning systems to join our team and help develop and deploy AI-driven functionality for a next-generation ophthalmic surgery robotic platform.

We welcome applications from individuals with experience in:

• Computer vision and image-based understanding
• Machine learning and data-driven systems
• Software development for robotics or real-world systems
• Data pipelines, model training, and deployment (MLOps)

This post will be embedded in the School of Biomedical Engineering & Imaging Sciences, a vibrant community of engineering focused on developing and clinically translating cutting-edge healthcare technologies. The successful candidate will join a highly interdisciplinary team working at the interface of robotics, software, and clinical practice, contributing to the development of AI-enabled capabilities for a first-in-class surgical robotic system with direct patient impact.

About the role:

We are looking for someone with a passion for translating advanced machine learning and computer vision methods into real-world systems as part of a small dynamic team of robotics and software engineers. The successful applicant will develop and deploy perception and learning-based components for surgical robot autonomy, contributing directly to the evolution of our in-house vitreoretinal surgical robotic platform.

Revitalise is a micro-surgical robot under development for precise therapy delivery in the back of the eye – the retina. The robotic system and software have been under development for over 7 years, and the team has now the expertise and funding to take the system to its first Clinical Investigation. The system enables increased dexterity inside the human eye using flexible curved instruments rather than conventional straight ones, creating unique challenges for vision-based control and automation in highly constrained environments.

In this role the successful candidate will work closely with robotics and software engineers to design, implement, and integrate computer vision and machine learning models for scene understanding and task automation. This includes developing robust perception pipelines, working with real experimental data, and ensuring that models perform reliably under real-world conditions.

Revitalise’s software is already using industry-standard practices including version-controlled codebases, testing, and continuous integration. The successful candidate will contribute to and extend these practices to machine learning workflows, including data management, model training, evaluation, and deployment (MLOps).

This is not a pure research role. The focus is on building reliable, maintainable, and deployable AI systems that integrate with robotic platforms and can support clinical translation. The successful candidate will therefore work across the full lifecycle from data and models to integrated system behaviour.

This is a full-time post (35 Hours per week), and you will be offered a fixed-term contract until 31/7/2028

About you:
(the candidate)

To be successful in this role, we are looking for candidates to have the following skills and experience:

Essential criteria

1. Degree (or equivalent experience) in computer science, robotics, engineering, or a related discipline.
2. Strong programming skills in Python, with experience in developing and maintaining structured codebases.
3. Experience in computer vision or machine learning, particularly for image-based understanding (e.g. detection, segmentation, tracking).
4. Experience working with modern ML frameworks (e.g. PyTorch, TensorFlow or equivalent).
5. Experience in building or working with data pipelines, including dataset preparation, evaluation, and iteration cycles.
6. Experience integrating software components into larger systems, ideally involving robotics, real-time systems, or hardware interaction.

We are able to offer sponsorship for candidates who do not currently possess the right to work in the UK.