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Role Description

As a Senior Machine Learning Engineer, you will lead the development and optimisation of an AI model for the Kinetic Edge Assistant (KEA), focusing on vision-to-text processing. Reporting to the CTO, you will drive the TRL3 phase objectives, including proof-of-concept model training and integration with the KEA software stack and associated edge hardware. This role is pivotal in ensuring on-device AI performance meets clinical standards for accuracy, latency, and reliability, while contributing to scalable, GDPR-compliant solutions. The position is fully-remote, based in the UK, fixed-term for three months starting in January 2026 with potential to extend.

Key Responsibilities

• Design, train, and fine-tune a machine learning model using pre-trained architectures.
• Collaborate on data annotation and curation, leveraging simulated and real-world surgical datasets to support iterative model refinement.
• Integrate AI components with the custom Android Open Source Project (AOSP) software stack, incorporating experiment tracking and CI/CD.
• Develop secure cloud integration pipelines for encrypted data uploads (AES-256/TLS 1.3), enabling GDPR-aligned storage, processing, and feedback loops for model improvement.
• Collaborate on benchmarks and validations, including structured feedback from surgical professionals.
• Mentor junior engineers and contribute to innovations.
• Support cross-functional efforts with external partners for TRL4 ML development and hardware prototyping.

Requirements

• Bachelor\'s or Master\'s degree in Computer Science, Artificial Intelligence, or a related field preferred but not necessary if relevant work experience and achievements can be shown.
• 5+ years of experience in machine learning engineering, with a focus on computer vision and natural language processing for edge devices.
• Proficiency in Python, PyTorch, and Hugging Face Transformers; experience with on-device optimisation (e.g., TensorFlow Lite, ONNX) and NPU acceleration.
• Strong knowledge of data pipelines, annotation tools (e.g., Roboflow), and cloud platforms (e.g., Kubernetes).
• Some familiarity with Android development, AOSP customisation, and security standards (GDPR, encryption protocols).
• Demonstrated ability to deliver production-ready ML systems in resource-constrained environments, with a track record of >95% model accuracy in real-time applications.
• Excellent problem-solving skills and experience in healthcare or regulated industries is advantageous.
• UK work eligibility required.

What We Offer

• Annual salary equivalent of £75,533 (pro rata for 51 day contract: £14,816), plus equity if contract is extended.
• Potential to extend beyond three month contract to full-time position upon project completion.
• Fully remote working arrangements with discretionary travel for collaborations if practical (e.g., to visit our partner UK HE organisation, ECM facilities etc.).
• Professional development opportunities, including access to our partner UK HE organisation resources and international partnerships.
• Contribution to meaningful impact: improving healthcare efficiency and outcomes through AI innovation.