Artificial Intelligence​/Machine Learning Engineer

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.

• 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.

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.

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.

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.

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.

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