Position Summary
We have an exciting opportunity available for an AI/ML Engineer to join us in the Technology Incubation Lab here at Samsung Research UK.
The Technology Incubation Lab is dedicated to developing and validating cutting-edge solutions in health and accessibility, bridging the gap between early-stage research and the commercialization of Samsung products. The lab works on externally funded projects, collaborating with academia, industry, and public sector organizations to explore next-generation technologies before they are integrated into commercial offerings. The team's core focus areas include developing AI-powered predictive healthcare solutions that integrate real-world health data from wearables, IoT devices, and medical records to enhance early disease detection and personalized health monitoring, as well as creating AI-powered accessibility solutions that improve digital and physical accessibility for individuals with disabilities, particularly in vision and cognitive support.
This role is available on a 12 month fixed term contract basis.
Role and Responsibilities
* Develop and optimize machine learning models for disease prediction, early diagnosis and personalised healthcare solutions.
* Process and analyze structured and unstructured health data (EHR, Wearables, HL7/FHIR) and implement deep learning algorithms for predictive healthcare applications.
* Contribute to research on AI-driven personalization strategies to empower users in managing their health effectively.
* Develop AI-powered accessibility solutions for Samsung products, leveraging multi-modal AI (text, image, audio).
* Adhere to data privacy regulations (GDPR, MDR, HIPPA, EHDS) and implement ethical AI practices.
* Work with multidisciplinary teams to translate technical insights into actionable solutions for stakeholders.
* Maintain clear documentation and deliverables for EU projects, ensuring transparency and accountability.
Skills and Qualifications
Essential:
* A PhD in the related field with a good level of work experience, or a Master's Degree with extensive work experience in the related field.
* Good understanding of cardiovascular diseases, risk factors and clinical workflows.
* Expertise in handling missing data, outliers and feature engineering.
* Experience in processing Health data from various sources (EHR, Wearables) and formats (e.g., HL7/FHIR, CSV, PDF, PNG, JPEG).
* Skilled in analysing time-series data from wearable sensors or medical devices (e.g., ECG, PPG).
* Proficient in hypothesis formulation, testing and correlation analysis using Python.
* Experience with supervised/unsupervised learning and model interpretability (e.g., SHAP, LIME).
* Skilled in creating clear visualizations with Matplotlib or Seaborn.
* Expertise in metrics like AUC-ROC, precision, recall, and cross-validation techniques.
* Experience deploying predictive models in clinical settings or EHR systems.
Desirable:
* Familiarity with healthcare regulatory frameworks (GDPR, MDR, HIPAA, EHDS).
* Ability to work with diverse teams and communicate technical insights effectively.
* Knowledge of Deep Learning, Reinforcement Learning and Federated Learning architectures.
* Familiarity with cloud platforms (AWS, GCP, Azure) and big data tools.
* Expertise in XAI, bias mitigation and ethical AI practices for healthcare.
* Experience with text, image and audio AI for accessibility applications.
Soft Skills:
* Strong skills in clear documentation and reporting skills for EU project deliverables
* Enthusiasm for AI applications in healthcare, energy and digital inclusion
* Self-learner with ability to work independently and contribute effectively
* Ability to thrive in dynamic environments, adapt to changing project requirements and meet deadlines effectively.
Employee Benefits:
* Highly competitive salary with performance bonus up to 21.5%.
* Employer pension contributions of 8.5%.
* 25 days paid holiday (increasing to 30 with time served).
* Life assurance, medical insurance, and income protection.
* Flexible benefits scheme with £600 annually to spend on benefits.
* Samsung product discounts, subsidised employee restaurant, and free parking.
Location and Hybrid Working:
* The role is based at Samsung R&D Institute in Staines-upon-Thames, Surrey, UK.
* Samsung currently operates a hybrid working policy of 3 days onsite and 2 days working from home weekly
Samsung has a strict policy on trade secrets. In applying to Samsung and progressing through the recruitment process, you must not disclose any trade secrets of a previous employer
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