Top Machine Learning Jobs in Malaysia

The Data Scientist will conduct data mining, utilize machine learning for model building, analyze datasets, develop insights, and mentor team members.

The role involves developing machine learning models, integrating analytics into manufacturing systems, ensuring data quality, and delivering performance insights through dashboards.

Provide independent advisory services to identify control gaps in technology projects, focusing on governance, risk management, and business strategy.

Monitor and optimize ML models, automate workflows, collaborate across teams, troubleshoot ML systems, and promote MLOps best practices.

The Senior Machine Learning Engineer will design, develop, and maintain scalable ML systems, manage end-to-end ML workflows, and collaborate with cross-functional teams to drive ML engineering excellence.

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.

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

The role focuses on developing generative AI applications using LLMs, integrating solutions on AWS Bedrock, managing workflows, and ensuring AI model reliability and compliance.

As a Machine Learning Scientist Intern, you will develop and test machine learning models, analyze data, and implement solutions in real-world applications.

As a Machine Learning Engineer intern, you'll assist in developing ML models, managing datasets, monitoring experiments, and collaborating with senior engineers and data scientists in a fintech environment.

Design, build, validate and productionize ML models and automated data pipelines on Databricks and Microsoft Fabric. Perform large-scale data processing in SQL/Python, feature engineering, experiment design, model evaluation, monitoring, and documentation while collaborating with stakeholders and mentoring junior analysts.

The Machine Learning Engineer will design and build machine learning systems, maintain models, and automate workflows while collaborating with Data Scientists and MLOps Engineers.

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.