Top Machine Learning Jobs in Malaysia

Manage product lines to ensure factory meets commitments and priorities, develop recovery plans, and drive improvement in efficiency and execution through effective supply planning.

Develop, implement, and manage credit risk models for various segments, monitoring their performance, and ensuring compliance with model governance.

Lead the design and development of scalable systems, translating complex requirements into effective solutions, mentoring team members, and ensuring system performance and availability.

Lead payment risk operations, manage chargeback lifecycle, conduct fraud investigations, collaborate with cross-functional teams, and mentor a high-performing team.

As a Process Engineer, you will improve wafer yields, support production processes, and train Associate Engineers while enhancing process efficiency through data analysis and collaboration.

Designs and builds technical GTM experiments, demo applications, and integrations while collaborating with the founding team and early adopters. The role emphasizes fast iteration and collecting feedback.

The Field Application Engineer will serve as the primary technical contact for customers, focusing on implementing AI/ML hardware/software solutions, collaborating with teams, and ensuring customer success.

Assist with improving processes and wafer yields in semiconductor manufacturing and optimize production workflows for increased productivity.

As a Machine Learning Engineer (LLM), you will fine-tune models, design evaluation frameworks, deploy AI features, and collaborate with cross-functional teams to enhance linguistic interaction in financial services.

As a Machine Learning Engineer, you will architect and deploy AI models, collaborate with product teams, and optimize AI capabilities for production.

The role involves operationalizing and optimizing ML models, developing pipelines, collaborating with data scientists, and maintaining ML services in production.

Contribute to the design and rollout of ML & AI platforms. Write production code and develop scalable ML pipelines and automation.

This role involves designing and implementing machine learning platforms, coding, code reviews, and automating ML pipelines for large-scale workloads.

Lead the Machine Learning Engineering team, architecting and deploying innovative AI platforms, while ensuring scalability and efficiency across Grab's services.

The Senior AI/ML Engineer at Nansen will develop AI models for blockchain data analysis, collaborating with teams to enhance platform capabilities and mentor junior engineers.

The Software Engineer will develop complex engineering solutions for job personalisation, collaborate with teams, and ensure high service availability while implementing scalable systems.

Design and implement Generative AI applications and scalable AI solutions using Azure. Collaborate across teams to solve business challenges and innovate with AI frameworks.