AI Engineer / Senior AI Engineer (Innovation) for AI Singapore
National University of Singapore
- Singapore
- Permanent
- Full-time
The AI Engineer (Innovation) plays the role of technical lead on an industry AI project, working with a team of apprentices to build the end-to-end AI solution for a client, while supported by a project manager and AI/MLOps heads.This role is suitable for engineers who enjoy a mix of technical development, client interaction and being the lead of a small project team.
- Assist our presales consultants to scope and define AI projects based on problem statements from clients, while applying design thinking practices.
- Lead a group of 3-4 apprentices on the development of the AI solution, applying best practices in the following areas: solution design and planning, data requirements definition, exploratory data analysis, ML model training, experiment tracking, pipeline building, containerisation, deployment testing, code repository management, and technical documentation.
- Mentor and coach apprentices who are learning to develop real-world AI solutions. Lead review/planning sessions and stand-ups.
- Communicate and consult with client stakeholders throughout the development lifecycle, to ensure their requirements are translated accurately and our technical choices are bought into by them.
- Keep abreast of and test emerging ideas in the areas of MLOps, robustness, fairness, explainability and security.
- Assist to update technical training materials for AISG's AI Apprenticeship Program, covering fundamentals in machine learning, deep learning and engineering. Be part of the team conducting the training and mentoring of batches of apprentices in their 8-week deep-skilling program.
- Support AI Singapore's industry and community-building activities by contributing to talks, article writing, and other outreach programmes.
- Degree in a quantitative field is preferred.
- At least 2 years of hands-on experience developing AI/ML solutions in a corporate or research setting. Solutions that have been deployed into production will be viewed favourably, especially if the candidate assisted in the integration and testing.
- Solid understanding of machine learning/deep learning fundamentals. Able to appreciate and explain the mathematical workings of common algorithms for computer vision/NLP/tabular data.
- Knowledge of techniques and developments in the area of Generative AI. Experience in building GenAI solutions is a plus.
- Hands-on skills in Python-based AI/ML frameworks, specifically PyTorch, TensorFlow and scikit-learn, with a demonstrated ability to adhere to clean coding principles.
- Experience working with software development tools such as Git and Docker. Prior exposure to Linux environments and CI/CD processes is an advantage. Familiarity with MLOps toolkits for productivity, tracking and reproducibility is a bonus.
- Aptitude for data story-telling, visualisation and technical communications. Able to abstract and convey technical concepts to non-technical audiences well.
- Team player with a keen interest in mentoring and collaborative problem-solving.
- Self-learner with a strong sense of curiosity and attention to detail.