The Digital Health Lab at Samsung is looking to solve the problem of creating the future of wellness and clinical care using user-centric design thinking and agile designer-developer workflow.
Requirements
Strong expertise in machine learning techniques, especially the algorithms related to recommendation systems (e.g. NCF, RNN, CNN etc)
Proficiency in Python, R, or Java
Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
Knowledge of data processing tools (e.g., Pandas, NumPy)
Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure)
Responsibilities
Design, build, and optimize machine learning models for recommendation systems
Implement algorithms such as supervised learning, unsupervised learning, reinforcement learning, and deep learning for health applications
Collect, clean, and preprocess large datasets for model training. Develop robust algorithms to extract meaningful insights
Debug and optimize models for better accuracy and efficiency using cloud-based service (e.g. AWS)
Collaborate with multidisciplinary teams to understand business requirements and translate them into technical solutions. Work with SW Engineering team to validate and improve model accuracy
Contribute to the development of novel ML algorithms to address complex healthcare challenges
Actively engage in team discussions, fostering a collaborative and inclusive work environment
Other
Master’s or PhD (near completion) experience in Computer Science, Machine Learning, Data Science, or a related field
Demonstrated ability to work collaboratively in multidisciplinary teams with strong problem-solving skills, attention to detail, and effective communication
Ability to sit and stand at a desk, communicate in person and by telephone, and frequently operate standard office equipment, such as telephones and computers
Must not disclose any trade secrets of a current or previous employer
Equal Employment Opportunity for all individuals regardless of race, color, religion, gender, age, national origin, marital status, sexual orientation, gender identity, status as a protected veteran, genetic information, status as a qualified individual with a disability, or any other characteristic protected by law
