About this role
Headquartered in Singapore, Actxa Pte Ltd is a deep tech company founded in 2015 that leverages artificial intelligence to create next generation preventive healthcare solutions.
We create evidence-based, personalized health insights in the domains of physical activities, sleep quality, body composition, stress and recovery, heart health and blood glucose evaluation and monitoring.
To improve population health, Actxa establishes worldwide partnerships and research collaborations to develop critical preventive health models to help people avert chronic diseases such as diabetes and hypertension.
We believe in positively impacting the lives of people around us and the environment we live in through the use of technology. Hence, we are committed to providing a conducive environment for all employees to realize their full potential, who in turn have the opportunity to continuously drive innovation.
We have opportunities for you to grow your career path and are looking for talented professionals to join our team.
What will you do?
- Research and develop algorithms that turn wearable sensor data (e.g. PPG, accelerometer, heart rate variability) into insights on activity, sleep, stress, recovery and heart health
- Build and improve models for blood glucose estimation and nutrition, including food recognition and nutrition data pipelines
- Develop generative AI and LLM-based features such as personalized health insights, conversational coaching and behavioral nudging
- Help design and run research studies with clinical and academic partners, covering protocol preparation, data collection and data quality checks
- Clean, organize and analyze health datasets using statistical modelling, machine learning and deep learning methods
- Test and validate algorithms and AI model outputs against reference data, and document methods and results clearly
- Work with software engineers to bring models into Actxa's apps and products
- Use AI-assisted tools (e.g. coding assistants, AI research agents) in day-to-day research and development, while critically validating their outputs
- Contribute to research publications and invention disclosures
Requirements
- Bachelor's or Master's degree in Data Science, Computer Science, Computer Engineering, Biomedical Engineering, Statistics or a related discipline
- 0 to 2 years of relevant experience; fresh graduates with strong internship or project experience are welcome
- Good working knowledge of Python and SQL, and libraries such as pandas, NumPy, scikit-learn and PyTorch or TensorFlow
- Solid foundation in statistics and machine learning
- Experience with signal processing or time-series data from wearables is a plus
- Familiarity with LLMs, prompt engineering, or frameworks such as Hugging Face, LangChain or LLM APIs is a plus
- Exposure to clinical or health research, or to glucose and nutrition data, is a plus
- Keen interest in digital health, wellness and preventive healthcare
- Able to explain findings clearly to non-technical colleagues
- Positive, adaptable and comfortable in a small team where priorities can shift
- A natural tenacity, resilience and determination