Senior AI/ML Engineer

Ambition Singapore; Singapore; On-site; SGD 70,000 - 90,000; Full time

Job summary

A leading recruitment firm in Singapore is searching for an experienced AI/ML Engineer with a solid background in machine learning and data science. Candidates should hold a Bachelor's or Master's degree and possess over 8 years of experience in software development with a strong focus on AI roles. Familiarity with Python, various ML tools, and cloud platforms is essential. The ideal applicant will have expertise in the full ML lifecycle and possess excellent communication skills to relate technical concepts to non-technical stakeholders.

Qualifications

• 8+ years of experience across software development, data science, and machine learning.
• At least 3+ years in AI engineering roles.
• Proven expertise in the full ML lifecycle.

Skills

Machine learning

Data science

Python programming

MLOps

CI/CD pipelines

Cloud platforms (GCP or AWS)

Education

Bachelor's or Master's degree in AI/ML or Data Science

Tools

pandas

scikit-learn

TensorFlow

PyTorch

Docker

Kubernetes

MLflow

Airflow

Kubeflow

Job description

• Holds a Bachelor's or Master's degree in AI/ML or Data Science, with a demonstrated ability to design and build machine learning models.
• Possesses 8+ years of experience across software development, data science, and machine learning, including at least 3+ years in AI engineering roles.
• Proven expertise in the full ML lifecycle-data preparation, model development, deployment, and ongoing monitoring.
• Strong proficiency in Python and solid understanding of AI/ML techniques, including LLMs and libraries such as pandas, scikit-learn, TensorFlow, and PyTorch.
• Hands‑on experience with LLM orchestration frameworks such as LangChain, LangGraph, vLLM, or LMDeploy.
• Strong knowledge of NoSQL databases; experience with graph databases is an added advantage.
• Familiarity with MLOps platforms like MLflow, Airflow, Kubeflow, or equivalent tools.
• Experience working with cloud platforms (GCP or AWS) for AI solutioning and ML deployment.
• Knowledge of core data science methods, including supervised/unsupervised learning, NLP, and time‑series analysis.
• Experience building and managing CI/CD pipelines, as well as containerization using Docker and Kubernetes.
• Strong understanding of AI governance, model risk management, and relevant regulatory frameworks.
• Ability to convey complex technical ideas to stakeholders without technical backgrounds.