AI Engineer (Full Stack)

JOBSTER PRIVATE LTD.; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A leading tech firm in Singapore is seeking an AI Solutions Developer with a strong background in machine learning. You will collaborate with various internal teams to develop and optimize AI solutions. The ideal candidate has at least 2 years of experience, a Bachelor's Degree in Computer Science or related fields, and is proficient in Python and cloud technologies. This position offers exciting challenges and opportunities for professional growth in a dynamic environment.

Qualifications

• Minimum 2 years experience in machine learning or data-heavy roles.
• Strong analytical thinking and eagerness to learn new technologies.
• Ability to work collaboratively in interdisciplinary teams.

Responsibilities

• Develop AI solutions with internal user groups and WOG agencies.
• Design and develop full-stack applications that serve user needs.
• Optimize performance of deployed AI systems.

Skills

Machine learning algorithms

Python (scikit-learn, TensorFlow, PyTorch)

SQL

Experience with vector databases

Cloud infrastructure deployment

Docker and Kubernetes

Data quality standards

Education

Bachelor’s Degree in Computer Science or Data Science

Tools

Docker

Kubernetes

Job description

What you’ll do:

• Develop Artificial Intelligence (AI) solutions domain by working collaboratively with internal user groups (Planners, Architects, Data Engineers, Data Scientists, UX Designers, Software Developers, etc.) and WOG agencies in the scoping, architecting, development, deployment and integration of machine learning or AI solutions using cloud or on-premise infrastructure
• Design and develop robust, scalable, and secure full‑stack applications that serve real user needs
• Write clean, maintainable, and well‑tested code across frontend, backend, and infrastructure layers
• Contribute to technical design discussions, architecture reviews, and engineering best practices
• Take ownership of features from conception through deployment and ongoing maintenance
• Assess the technical feasibility of proposed AI initiatives, estimate resource requirements, and identify potential risks or challenges to make informed decisions about which AI projects to pursue and how to prioritise development efforts
• Responsible for monitoring and optimising the performance of deployed AI systems, including identifying bottlenecks, implementing efficiency improvements, and ensuring that systems can handle production workloads effectively whilst maintaining acceptable response times and resource utilisation
• Evaluate new algorithms, frameworks, and methodologies to determine their potential application within the organisation
• Support the training of company community in the use of AI technologies
• Engage stakeholders across departments and external agencies to gather use cases and requirements, document user feedback, and support solution roll‑outs with feedback loops

Requirements:

• Have a keen interest in cities and in applying expert knowledge and expertise to develop AI/ML‑enabled solutions that will enable Planners to make Singapore an even more liveable, sustainable and economically competitive city.
• Bachelor’s Degree or higher in Computer Science, Data Science, or related disciplines. We will also factor in relevant certifications (e.g., Coursera).
• At least 2 years of relevant experience, in machine learning engineering, data science, data engineering, or other data‑heavy roles, and proficiency in the following:
  1. Common machine learning algorithms and key parameters, Natural Language Processing, Knowledge‑based Systems (KBS) and Generative AI projects.
  2. Developing and optimising machine learning or AI models using common Python packages such as scikit-learn, TensorFlow, or PyTorch.
  3. SQL and/or experience working with vector databases (such as Pinecone, Weaviate, Chroma, or similar) for similarity search, embeddings storage, and retrieval‑augmented generation (RAG) applications.
  4. Working with cloud infrastructure and services to deploy machine learning models, pipelines, or solutions (e.g. Microsoft Azure/AWS)
  5. Containerization technologies such as Docker and orchestration platforms like Kubernetes, with a strong understanding of deploying and managing machine learning models in containerised environments.
  6. Capable of architecting machine learning or AI solutions that meet the users’ needs while being effective, reliable, secure, scalable, and cost‑efficient.
  7. Capable of cleaning, imputing, and correcting anomalies in the collected structured or unstructured data to ensure high data quality standards.
• Ability to work well in cross‑functional and interdisciplinary teams, e.g with engineers and data scientists in development and training of ML models.
• Strong analytical thinking and eagerness to learn and share new technologies with team members
• Strong communication skills and ability to work collaboratively

Preferences:

• Understanding or experience in machine learning or AI governance, especially in explainability and fairness.
• Experience in delivery of machine learning or AI solutions for internal teams or external clients