IMDA CLT - Machine Learning Engineer

TRAINOCATE (S) PTE. LTD.; Singapore; On-site; SGD 50,000 - 80,000; Full time

Job summary

A leading tech firm in Singapore is seeking a Machine Learning / AI Engineer to develop and optimize advanced AI and machine learning solutions. The role involves collaborative work with cross-functional teams to drive innovation in product capabilities. Candidates should have experience in developing machine learning models, integrating AI into products, and monitoring models in production environments. Stay updated with emerging AI technologies and apply best practices in this exciting position.

Qualifications

• Experience in developing and deploying machine learning models.
• Familiarity with AI technologies such as computer vision and natural language processing.
• Ability to optimize model performance.

Responsibilities

• Design, develop, and maintain machine learning models.
• Collaborate with teams to integrate AI solutions.
• Deploy and monitor AI models in production.
• Optimize performance, scalability, and reliability.
• Stay updated on emerging AI technologies and apply best practices.

Job description

Job Description

AWS Career Launchpad with Trainocate Supports fresh graduates and mid-career professionals — specifically Singaporeans and Permanent Residents (PRs). This contract for service opportunity allows you to enter tech or pivot within.

As a Machine Learning / AI Engineer or MLOps Engineer, you will develop, deploy, and optimize advanced AI and machine learning solutions that transform product capabilities and enhance user experiences. You will work collaboratively with cross-functional teams to build scalable AI systems using cutting-edge technologies like computer vision, natural language processing, and generative AI, driving innovation and business growth.

Job Responsibilities

• Design, develop, and maintain machine learning models and pipelines.
• Collaborate with teams to integrate AI solutions into products and services.
• Deploy and monitor AI models in production environments.
• Optimize model performance, scalability, and reliability.
• Stay updated on emerging AI technologies and apply best practices.