AI Engineer — Defense Data Science & ML Ops Lead

MINDEF; Singapore; On-site; SGD 80,000 - 140,000; Full time

Job summary

MINDEF is seeking a data science and AI engineering professional to lead projects across the full lifecycle, from conception to deployment, ensuring results drive policy, operations, and resource decisions.

You will collaborate with business and technical counterparts to translate insights into actionable recommendations while maintaining responsible AI practices and high-quality documentation.

Qualifications

• Education in Statistics, Machine Learning, Computer Science, Operations Research, or related field.
• 1+ year of work experience in data science, AI, or AI engineering role.
• Experience with LLMs, agentic AI frameworks, and design patterns is advantageous.
• Experience with MLOps on commercial cloud platforms is advantageous.
• Proficiency in Python, R, or SQL and ML libraries like PyTorch/TensorFlow.
• Curious, creative, and detail-oriented problem solver.
• Able to work in a fast-paced, collaborative environment.
• Strong communication to explain complex concepts to non-technical stakeholders.

Responsibilities

• Lead data science and AI projects across the full lifecycle from conceptualization to deployment.
• Design, develop, and deploy AI solutions translating insights into actionable recommendations.
• Identify AI use cases with business partners and build proofs-of-concept to demonstrate value.
• Uphold standards for data prep, modeling, deployment, and monitoring; explore new techniques.
• Document methods, parameters, deployment configurations, and validation steps.

Skills

Python

R

SQL

PyTorch

TensorFlow

LLMs

MLOps

Education

Statistics

Computer Science

Operations Research

Tools

PyTorch

TensorFlow

HuggingFace

Job description

MINDEF is seeking a data science and AI engineering professional to lead projects across the full lifecycle, from conception to deployment, ensuring results drive policy, operations, and resource decisions.

You will collaborate with business and technical counterparts to translate insights into actionable recommendations while maintaining responsible AI practices and high-quality documentation.