Senior AI/ML Engineer (JD#10701)

SCIENTE INTERNATIONAL PTE. LTD.; Singapore; On-site; SGD 100,000 - 140,000; Full time

Job summary

A leading tech consulting firm in Singapore is looking for a Senior AI Engineer to design and deliver AI solutions for the banking industry. This role requires collaboration with various teams to build secure AI systems. Ideal candidates will have extensive experience in AI engineering, a strong background in Python and AI/ML frameworks, and knowledge of MLOps practices. Responsibilities include model deployment and ensuring compliance with AI policies. Competitive compensation offered.

Qualifications

• 8+ years of experience in software development, data science, or ML engineering.
• 3+ years in dedicated AI engineering roles.
• Experience with supervised/unsupervised learning and NLP.

Responsibilities

• Collaborate with business stakeholders to define AI solutions.
• Engineer and maintain ML models in production.
• Document ML workflows and governance controls.

Skills

Software development

Machine learning engineering

Data processing

Python

AI/ML frameworks

Large Language Models (LLMs)

NoSQL databases

MLOps platforms

Cloud platforms (GCP or AWS)

CI/CD practices

Docker

Kubernetes

Education

Bachelor’s or Master’s in AI, ML, Data Science, or related field

Tools

TensorFlow

PyTorch

scikit-learn

MLflow

Airflow

Kubeflow

Job description

Job Summary

We are seeking a Senior AI Engineer to join a growing engineering team to design, build, and deliver next-generation AI solutions for enterprise projects in banking industry. In this role, you will collaborate with business stakeholders, data teams, and platform engineering groups to develop scalable, secure, and responsible AI systems.

Mandatory Skill-set

• Bachelor’s or Master’s degree in Artificial Intelligence, Machine Learning, Data Science, Computer Science, or a related field;
• Must have 8+ years of experience in software development, data science, or ML engineering,
• Must have 3+ years in dedicated AI engineering roles;
• Proven experience across the full ML lifecycle: data processing, model development, deployment, monitoring, and optimization;
• Must have experience in Python and widely used AI/ML frameworks such as pandas, scikit-learn, TensorFlow, PyTorch, and others;
• .Hands-on experience working with Large Language Models (LLMs) and orchestration frameworks such as LangChain, LangGraph, vLLM, or LMDeploy;
• Solid understanding of NoSQL databases;
• Experience with MLOps platforms such as MLflow, Airflow, Kubeflow, or similar;
• Familiarity with modern cloud platforms (GCP or AWS) for AI development and deployment;
• Knowledge of supervised/unsupervised learning, NLP, time-series modeling, and related data science techniques;
• Experience with CI/CD, Docker, and Kubernetes;
• Strong understanding of AI governance, model risk management, and related regulatory frameworks.

Desired Skill-set

• Experience with Responsible AI frameworks, fairness/bias assessment, and model explainability tools;
• Exposure to graph databases;
• Exposure to feature stores, model registries, and data/version management tools;
• Understanding of data privacy, anonymization, and compliance requirements in regulated industries.

Responsibilities

• Collaborate with business stakeholders to understand use cases, define AI solution approaches, and build Proofs of Concept (PoCs) when required;
• Engineer, deploy, and maintain machine learning models in production using best-in-class MLOps practices (model versioning, CI/CD, observability, monitoring and others;
• Build and maintain scalable, maintainable data pipelines and monitor model performance across environments;
• Ensure all AI solutions comply with organizational AI policies, responsible AI guidelines, and audit/regulatory requirements;
• Support data exploration, feature engineering, and hands-on model development when necessary.
• Automate model retraining, testing, evaluation, and performance monitoring workflows;
• Document ML workflows, governance controls, and model risk assessments;
• Partner with CloudOps, DevOps, IT, and Security teams to successfully integrate AI solutions into enterprise platforms;
• Contribute to continuous improvement of engineering standards, automation, and reusable AI components.

Should you be interested in this career opportunity, please send in your updated resume to [e-mail] the earliest.

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Confidentiality is assured, and only shortlisted candidates will be notified for interviews.

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