Artificial Intelligence / Machine Learning Engineer - 12 Month Fixed Term Contract

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 • Please visit Samsung membership to see Privacy Policy, which defaults according to your location, at: https://account.samsung.com/membership/policy/privacy. You can change Country/Language at the bottom of the page. If you are European Economic Resident, please click here: https://europe-samsung.com/ghrp/PrivacyNoticeforEU.html