AI Engineer

SAGL Consulting; Singapore; On-site; SGD 70,000 - 120,000; Full time

Job summary

A leading consulting firm in AI/ML is seeking an AI/ML Developer to design and develop machine learning models. The role involves collaboration with various teams, deploying models through MLOps frameworks, and maintaining AI systems while staying updated on industry trends. Ideal candidates will have a Bachelor's or Master's degree in relevant fields and 2-5 years of experience in AI/ML development.

Qualifications

• 2–5 years’ experience in AI/ML development.
• Good grasp of ML algorithms and software development best practices.
• Experience with data orchestration tools like Airflow and Kafka is preferred.

Responsibilities

• Design & Develop machine learning models for business applications.
• Collaborate with stakeholders to identify AI use cases.
• Deploy Models via MLOps pipelines and ensure model performance.

Skills

Python

TensorFlow

PyTorch

Scikit-learn

NumPy

Pandas

Education

Bachelor’s or Master’s in Computer Science, Data Science, AI, Engineering, or related fields

Tools

Docker

Git

Cloud platforms (AWS, GCP or Azure)

Job description

Main Responsibilities

• Design & Develop machine learning and deep learning models to power business applications
• Collaborate with stakeholders (data scientists, software engineers, product teams) to identify AI use cases
• Pre‑process Data / Engineer Features and refine models for optimal performance
• Deploy Models via MLOps pipelines (CI/CD, monitoring, version control)
• Maintain & Improve AI systems, ensuring scalability, robustness, and continuous refinement
• Stay Updated on latest AI research, tools, and industry trends

Job Requirements

Academic Qualifications:

• Bachelor’s or Master’s in Computer Science, Data Science, AI, Engineering, or related fields

Experience & Technical Skills:

• 2–5 years’ experience in AI/ML development
• Proficient in Python and ML libraries: TensorFlow, PyTorch, Scikit‑learn, NumPy, Pandas
• Good grasp of ML algorithms, data pipelines, software development best practices
• Experience with cloud platforms (AWS, GCP or Azure) for model training and deployment
• Familiar with Docker, Git, and CI/CD workflows

Preferred (but not mandatory):

• Exposure to NLP, Computer Vision, or Generative AI
• Experience with data orchestration tools like Airflow, Kafka
• Familiarity with MLOps frameworks (e.g., Kubeflow, MLflow)