Description
We are looking for enthusiastic iSTEM postgraduates to join our AI team in tackling complex, real-world challenges through the development of advanced algorithms and machine learning models. In this role, you will gain hands-on experience in data preparation, model development, testing, and cross-functional collaboration. You will also play a part in integrating AI solutions into our software products, helping to drive meaningful impact in the field of public safety. This is a unique opportunity to gain exposure to industry best practices, cutting-edge technologies, and modern coding standards.
The role offers a monthly stipend of SGD 2,200 for successful applicant.
Responsibilities
- Research and develop AI solutions across video, text, and audio domains, integrating state-of-the-art (SOTA) models into our services.
- Design and implement modular, maintainable, and scalable services to accelerate development.
- Contribute to system design and development in alignment with business needs.
- Evaluate model performance, conduct experiments, and fine-tune models to achieve optimal outcomes.
- Maintain clear, structured documentation of code, experiments, and findings.
- Collaborate with cross-functional teams to seamlessly integrate AI solutions into existing software products.
Requirements
- Currently pursuing a Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Strong programming skills in Python, Typescript/JavaScript or another relevant programming language.
- Proficiency in data structure and working knowledge of basic SQL queries.
- Foundational understanding of machine learning concepts and algorithms.
- Strong problem-solving and analytical skills.
- Excellent communication and teamwork skills.
- Eagerness to learn and enthusiasm for contributing to impactful AI projects.
What sets you apart
- Exposure to cloud and containerization technologies (e.g., Docker, Kubernetes).
- Experience with or interest in AI-related technologies (e.g., NLP, computer vision, generative AI).
- Familiarity with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Ability to balance technical depth with practical implementation.