About the Role
We are seeking a highly motivated Data and Artificial Intelligence Scientist to design, develop, and deliver reusable, scalable, and cost-effective cloud-native data and AI solutions. As part of a multidisciplinary AI development team, you will explore, evaluate, and apply state-of-the-art AI technologies to solve complex real-world challenges across industries.
In this role, you will work closely with product owners, engineers, researchers, and industry partners to transform ideas into impactful products and services. From ideation and prototyping to deployment and operationalisation, you will play a key role in driving the adoption of data-driven and AI-driven innovations that can deliver meaningful outcomes for businesses, government agencies, and society.
This is an exciting opportunity for individuals who are passionate about machine learning and artificial intelligence, enjoy solving challenging problems, and are eager to contribute to Singapore's digital transformation journey.
Job Responsibilities
- Collaborate with product owners, engineering teams, and industry partners throughout the product development lifecycle, from concept and design to deployment, operationalisation, and end-of-life management.
- Evaluate the maturity, viability, and applicability of emerging AI technologies, research advancements, and industry trends.
- Design, develop, and deploy scalable AI and data solutions using cloud-native and microservices-based architectures.
- Build, test, and optimise machine learning, deep learning, and generative AI models for production environments.
- Develop and deploy AI-powered applications, including AI agents, Retrieval-Augmented Generation (RAG) systems, and knowledge-based solutions.
- Participate in agile and secure software development processes, including requirements gathering, technical documentation, testing, and code reviews.
- Propose, implement, and validate algorithms while ensuring both functional and non-functional requirements such as scalability, explainability, fairness, security, maintainability, and cost efficiency.
- Work with structured, unstructured, and multimodal datasets to develop innovative AI-driven solutions.
- Contribute technical expertise to cross-functional teams addressing industry-wide challenges through data and AI technologies.
- Stay current with advancements in AI, machine learning, large language models (LLMs), and related technologies, and identify opportunities for innovation.
Job Requirements
- Degree in Computer Science, Computer Engineering, Data Science, Mathematics, Statistics, Engineering, or a related discipline.
- Strong technical foundation in artificial intelligence, machine learning, and data science.
- Good understanding of modern AI technologies and the latest advancements in AI research for real-world deployment.
- Strong programming skills in Python and/or C++.
- Experience with data manipulation, visualisation, machine learning, and reporting libraries and frameworks.
- Hands-on experience with deep learning frameworks such as TensorFlow, PyTorch, or equivalent.
- Experience in prompt engineering and developing solutions using large language models (LLMs) such as OpenAI and Anthropic Claude.
- Hands-on experience designing and deploying AI agents, RAG applications, and vector and/or graph databases.
- Strong understanding of software engineering principles and experience building production-grade AI applications.
- Knowledge of cloud platforms, microservices architecture, and AI solution deployment practices.
- Strong analytical, problem-solving, and critical thinking skills.
Preferred Qualifications
- Understanding of 3D geometry, vector mathematics, and coordinate systems.
- Experience with mesh processing, geometric transformations, Boolean operations, or computational geometry algorithms.
- Familiarity with 3D modelling or CAD tools such as Blender, Revit, or equivalent platforms.
- Experience with graphics and geometry libraries such as OpenGL, CGAL, Three.js, or similar technologies.
- Experience working with multimodal AI, computer vision, spatial data, or digital twin applications.
- Ability to work effectively within cross-functional teams and collaborate with diverse stakeholders.
- Excellent verbal and written communication skills, with the ability to present technical concepts to both technical and non-technical audiences.