Job Description
Are you passionate about leveraging Artificial Intelligence to transform how we validate human potential? The Singapore Institute of Technology (SIT) is seeking a visionary Software Engineer to join our AI Systems team. In this role, you will be at the forefront of developing a cutting-edge Centralised Skills Assessment and Validation platform designed to support Singapore's workforce transformation.
You will work in a fast-paced, collaborative environment, bridging the gap between sophisticated machine learning models and practical, scalable software architecture. This position is ideal for an engineer who thrives on solving complex problems, building high-impact tools, and contributing to a national agenda that prioritizes lifelong learning and skills-based hiring.
As part of our mission, you will have the opportunity to design robust systems that ensure the integrity and accuracy of skills verification, impacting thousands of learners and professionals nationwide. If you are an innovator ready to build the future of AI-driven assessment, we want to hear from you.
Responsibilities
- Architect and implement high-performance AI-driven assessment modules within the centralised platform.
- Collaborate with cross-functional teams to integrate machine learning models into robust production-grade software.
- Develop and maintain secure, scalable APIs to facilitate seamless data exchange between assessment tools and educational databases.
- Implement rigorous validation frameworks to ensure fairness, accuracy, and efficiency in skills assessment algorithms.
- Optimize system architecture for performance, security, and high availability in a cloud-native environment.
- Engage in code reviews, technical documentation, and agile rituals to ensure high-quality software delivery.
- Provide technical leadership in troubleshooting and refining complex AI workflows.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
- Proven experience (3+ years) in software engineering, with a strong focus on AI/ML integration or data-intensive applications.
- Proficiency in Python and familiarity with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Strong background in cloud platforms (AWS, Azure, or GCP) and containerization technologies (Docker, Kubernetes).
- Deep understanding of RESTful API design, database management (SQL/NoSQL), and software testing methodologies.
- Experience with CI/CD pipelines and automated deployment processes.
- Excellent communication skills with the ability to translate complex technical concepts for non-technical stakeholders.