Top Machine Learning Jobs in Malaysia

The Technical Consultant will drive process improvements using AI, support strategic client implementations, and innovate payroll solutions through technology.

The AI Data Analyst is responsible for managing data to enhance AI solutions, developing algorithms, ensuring data quality, and providing insights to inform business strategies.

The intern will engage in full-stack development, collaborating with teams, optimizing code, and exploring AI techniques, while learning Agile methodologies.

As a Software Engineer, design, develop, and deploy software solutions leveraging AI. Optimize performance and collaborate with cross-functional teams to enhance customer experiences and internal efficiency.

As a Process Engineer, you will enhance production processes, improve wafer yields, support continuous improvement projects, and coach Associate Engineers while collaborating across teams.

As a Lead Data Scientist, you'll manage end-to-end projects, build and deploy AI models, analyze data, and collaborate with teams to enhance user experience.

The AI Data Specialist will assist in enhancing AI content through tasks like data collection, evaluation, annotation, and tagging across various media types.

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

Manage and mentor engineering teams, ensure high-quality product delivery, contribute to technical decisions, and enhance classroom learning experiences.

Develop and maintain credit risk models for Consumer, Small Business, and Wholesale segments. Monitor model performance and ensure compliance with governance frameworks while collaborating with stakeholders for analytical solutions in credit decisioning and strategy.

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

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.

As an AI/ML Agentic Engineer, you'll design autonomous AI agents, build multi-agent systems, and deploy predictive models while collaborating with stakeholders and advancing AI strategies.

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.

As an AI/ML Research Engineer, you'll fine-tune models, design datasets, evaluate performance, and collaborate to launch AI features, shaping a new consumer product.

As a founding Machine Learning Engineer, you will transform language models into impactful products, fine-tune models, design data pipelines, and collaborate on AI features, significantly influencing the product's technical direction.

As a Senior AI/ML Software Engineer, you will design, deploy, and manage machine learning models and infrastructure, collaborating with cross-functional teams to improve user experience in financial services.

The MLOps Engineer deploys ML models, manages cloud infrastructure, develops APIs, and ensures efficient ML solutions through collaboration with data scientists and engineers.

As an AI Technologist, you'll lead AI strategy and implementation, focusing on AI agent development, automation solutions, predictive analytics, and customer success enhancement across various platforms.

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.