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About 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. You will work alongside research scientists, engineers, and the clinical development team to shape both the algorithms and the platform that delivers them.

Responsibilities

Contribute architecturally and hands-on 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 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, and 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 software development and regulatory teams for efficient integration from R&D to deployment.

Requirements

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.

Skills

Machine Learning
Python
PyTorch
OpenCV
Pandas
SciPy
NumPy
SciKit-learn
Cloud platforms (AWS, GCP, or Azure)
MLOps tooling (MLflow, Weights & Biases, DVC, Airflow)
Version control
Code review
Software testing methodologies
Continuous integration
Hyperspectral image processing
Image reconstruction
Tissue characterisation
Semantic segmentation
Data pipelines
MLOps best practices
Model versioning
Model deployment
Model monitoring
Drift detection
Rollback
Reproducible training
Dataset governance
Experiment tracking
Model documentation

Location

London

Work Type

Hybrid working arrangements

Experience Level

Senior
6+ years industry experience

Education Level

PhD or MSc in Machine Learning, Physics, Mathematics, Computer Vision, or related technical discipline

Salary/Compensations

Competitive salary

Benefits

Equity participation via share option scheme
25 days of annual leave plus bank holidays
Employee Assistance Programme for wellbeing, legal, and financial support
Cycle to Work Scheme
Workplace Nursery Benefits
£150 annual tech stipend for productivity and office essentials
Complimentary office snacks and drinks
Monthly team socials

About the Company

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.
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.

Equal Opportunity

We are committed to creating an inclusive environment where a diverse mix of talented people come and enjoy working with each other.