ML/AI Engineer

EXCELTECH COMPUTERS PTE. LTD.; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

EXCELTECH COMPUTERS PTE. LTD. in Singapore's Paya Lebar area is seeking an ML/AI Engineer embedded in the Data Analytics and AI Division, working with the Fraud Analytics Model team to build scalable ML solutions.

You will design and deploy ML/LLM-enabled applications in production, collaborating with data engineers and product teams, and ensure governance, security, and observability. The ideal candidate has 3–5 years hands-on ML/AI experience, including at least one LLM-enabled deployment,

Qualifications

• 3–5 years hands-on ML/AI experience, with at least one LLM-enabled system deployed to production.
• Strong Python software engineering with API development, testing, version control.
• Experience with LLM applications, retrieval, tool use, and multi-agent frameworks.
• Experience integrating AI/ML with enterprise data platforms, databases, APIs, or cloud services.
• Ability to design evaluation frameworks including testing, benchmarking, observability and reproducibility.
• Knowledge of AI governance, security and Responsible AI practices including human-in-the-loop controls.

Skills

Python engineering

ML deployment

LLM applications

Multi-agent frameworks

API development

Security & governance

Observability

Tools

Bedrock

AWS S3

Redshift

Lambda

Databricks

PySpark

Docker

MLflow

GitHub Actions

Jenkins

Job description

ML/AI Engineer

Work location- Paya Lebar

The ML/AI Engineer is embedded within Data Analytics and AI Division (DSAD), working as part of the division's Fraud Analytics Model (FAM) team.

Experience: 3-5 years of hands-on experience building and deploying ML/AI applications. This must include at least one LLM-enabled system delivered beyond prototype into operational use.

B. Technical & Professional Competencies

• Strong Python software engineering capability, including API development, testing, version control and modular system design.
• Hands-on experience building and deploying ML/AI applications, including at least one LLM-enabled or agentic AI solution beyond proof-of-concept stage.
• Experience with LLM applications, retrieval, tool use, workflow orchestration or multi-agent frameworks such as LangGraph, CrewAI or equivalent.
• Experience integrating AI/ML solutions with enterprise data platforms, databases, APIs or cloud services.
• Ability to design and implement systematic evaluation frameworks for AI systems, including testing, benchmarking, observability and reproducibility.
• Working knowledge of AI governance, security and Responsible AI practices, including human-in-the-loop controls, access management, auditability and safeguards against misuse.

Preferred (Advantageous)

• Experience with AWS services such as Bedrock, Redshift, Glue, S3, Lambda or related cloud-native services.
• Experience with PySpark, Databricks or large-scale data processing and feature engineering pipelines.
• Experience with CI/CD, containerisation, MLOps or model deployment tooling (e.g. Docker, MLflow, GitHub Actions, Jenkins).