What the role is
The Government Technology Agency (GovTech) is the lead agency driving Singapore’s Smart Nation initiatives and public sector digital transformation. As the Centre of Excellence for Infocomm Technology and Smart Systems (ICT & SS), GovTech develops the Singapore Government’s capabilities in Data Science & Artificial Intelligence, Application Development, Smart City Technology, Digital Infrastructure, and Cybersecurity.
At GovTech, we offer you a purposeful career to make lives better. We empower our people to master their craft through continuous and robust learning and development opportunities all year round. Our GovTechies embody our Agile, Bold and Collaborative values to deliver impactful solutions.
GovTech aims to transform the delivery of Government digital services by taking an "outside-in" view, putting citizens and businesses at the heart of everything we do.
Play a part in Singapore’s vision to build a Smart Nation and embark on your meaningful journey to build tech for public good. Join us to advance our mission and shape your future with us today!
About The Video Analytics Team
As the Capability Center for data science and artificial intelligence, Data Science & Artificial Intelligence Division focus is in enabling data science and artificial intelligence solutions, products and capability building across the government.
We are looking for individuals passionate in delivering great digital experiences to join our team! As part of DSAID, the Video Analytics team strive to drive scalable, impactful AI-enabled video analytics deployments for our citizens and businesses.
What you will be working on
The Senior AI Engineer role will be responsible to develop and implement cutting-edge computer vision solutions to address complex challenges for public good.
- Research and Prototyping: Stay up-to-date with the latest advancements in computer vision and identify opportunities for their application in public sector challenges. Conduct rapid prototyping of computer vision solutions to perform feasibility studies.
- Computer Vision Solution Development: Lead the design, development, and deployment of AI-powered applications and systems to tackle real-world problems. Collaborate with cross-functional teams and work closely with government stakeholders and subject matter experts to understand requirements and convert them into practical and scalable AI solutions.
- Product Development: Work closely with the product team to shape the product roadmap and develop innovative Computer Vision features to enhance existing offerings or introduce new products
- Model Evaluation and Validation: Conduct systematic testing and evaluation of computer vision models to ensure accuracy, robustness, and generalisation on various real-world scenarios and datasets.
- MLOps Implementation: Establish and optimise MLOps workflows, including model versioning, automation, continuous integration, and continuous deployment, to enhance the efficiency of machine learning development and deployment processes.
- Mentorship and Knowledge Sharing: Act as a subject matter expert, provide guidance and mentorship to junior AI engineers, and actively contribute to knowledge sharing initiatives within the organisation.
What we are looking for
- Bachelor’s/Master’s/Ph.D degree in Computer Science, Engineering, or a related field, with a focus on artificial intelligence and machine learning.
- Minimum of 5 years of hands-on experience in developing and implementing AI solutions, with a strong track record of successful projects
- Familiarity with cloud computing platforms like AWS, Azure, or Google Cloud for AI model deployment
- Proficiency in programming languages such as Python, Javascript, C++, or similar.
- Hands-on experience with deep learning frameworks such as PyTorch and TensorFlow and computer vision libraries such as OpenCV and Scikit-Image.
- Strong expertise in optimising AI models using tools such as TensorRT for real-time or near real-time processing
- Demonstrated experience in implementing MLOps practices, including version control, automated testing, and continuous integration/continuous deployment (CI/CD) pipelines
- Familiarity with containerisation technologies like Docker, Docker Compose, Docker Registry.
- Hands-on experience with backend API and microservice development.
- Knowledge of edge computing, embedded systems, and IoT platforms is advantageous.
- Excellent communication skills to articulate technical concepts to non-technical stakeholders and collaborate effectively within multidisciplinary teams.