Senior Machine Learning Engineer
Role details
Job location
Tech stack
Job description
You will be a core member of the Applied AI team, developing AI systems that operate in real surgical environments.
This role focuses on delivering production-grade machine learning (ML) systems that enhance surgical precision, provide decision support, and enable new capabilities in robotic-assisted surgery.
You will work across the full lifecycle, from problem definition and data strategy through to deployment on real systems.
We combine cutting-edge robotics with AI to deliver real-world impact in the operating room. If you want to build systems that directly affect patient care, this is a rare opportunity to do so at scale.
Responsibilities
- Translate clinical and product needs into ML tasks, metrics, and evaluation frameworks.
- Select, adapt, and fine-tune the state-of-the-art ML models for the application.
- Define data requirements and dataset strategy
- Analyse model failures and drive targeted data improvements
- Work with domain experts to establish high-quality ground truth
- Collaborate with data and embedded software teams to deploy reliable models.
- Own end-to-end ML solutions from concept to production
- Communicate and document technical decisions and trade-offs clearly
Wed expect you to be willing to turn your hand to anything within the applied AI team remit that helps the team deliver its objectives.
Requirements
To be successful in this role, youll need to have/be:
- Degree in a STEM field (e.g. Computer Science, Engineering, Mathematics, Statistics, Physics, Robotics) or equivalent experience.
- Experience developing and deploying machine learning models, ideally in computer vision or multimodal systems
- Experience with data curation, augmentation, and error analysis.
- Experience with model deployment and optimisation for performance (e.g. latency, memory), on edge or cloud environments
- Strong hands-on experience with Python and modern ML frameworks (e.g. PyTorch or TensorFlow).
Desired, but not essential:
- PhD or masters in computer science, machine learning, mathematics, statistics, engineering, physics, robotics or relevant fields.
- Experience in robotics, medical devices, or other safety-critical domains.
- Experience with LLMs, multimodal models, VLAs or foundation model adaptation.
- Familiarity with LoRA, distillation, or other efficient fine-tuning methods.
- Track record of solving ML problems under real-world constraints.
- Open-source, publication, or technical leadership contributions.
- Experience with C++, Linux, Nvidia Jetson, IGX platforms and Holoscan SDK
Benefits & conditions
We offer a competitive salary and a great benefits package including a bonus, pension, healthcare and enhanced global parental leave pay.