Top Machine Learning Jobs in Malaysia

As a Data Associate, you will label images of retail products, capture photos, manage datasets, and ensure data quality while maintaining high labeling accuracy.

Lead and optimize manufacturing operations using digital technologies (automation, analytics, simulation, ML). Serve as technical specialist and project lead, drive continuous improvement, mentor teams, support customers, and implement digital solutions to improve production efficiency, quality, and cost.

The Junior Wind Engineer will analyze wind loading on various structures, solve engineering problems, and support project delivery and business development.

The Sales Manager will drive customer acquisitions and revenue growth, manage complex sales cycles, and present Cloud solutions at executive levels while maintaining long-term relationships with clients.

The IT Consultant will design SAP FI/CO solutions, lead automation initiatives, manage projects, and ensure testing excellence while providing ongoing support.

The intern will develop AI models, enhance neural mechanism understanding, and collaborate on generative modeling while maintaining code quality.

The Process Engineer drives process optimization and continuous improvement initiatives using Lean Six Sigma methodologies to enhance manufacturing quality, cost, yield, and productivity.

Design, build, and deploy AI/ML and GenAI solutions (LLMs and AI agents) for IT automation and AIOps. Lead solution ownership in Agile, develop/run machine learning models, integrate open-source and proprietary LLMs, build runbook executors (PowerShell/Python), work with cloud and container platforms, engage stakeholders, and document automation and models.

Design, build, and deploy production ML models and MLOps pipelines for fraud and AML detection across batch and real-time scoring. Collaborate with engineering and data teams on feature engineering, optimize low-latency model performance, run validation and A/B tests, and mentor junior engineers while aligning to architecture standards.

Support data pipelines and ML workflows for manufacturing: apply computer vision and ML to detect defects, build and deploy models (APIs/edge), design GenAI/LLM applications, and collaborate with stakeholders to improve yield and quality.

The Power ML Engineer will tailor existing models for the Japanese power market, integrate market signals, develop features, monitor performance, and work collaboratively on product roadmaps.

The Machine Learning Engineer will design and deploy scalable machine learning systems, build data pipelines, optimize model performance, and ensure integration with existing infrastructure while collaborating with cross-functional teams.

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

Design, build, deploy, and maintain scalable ML systems and productionized models. Own end-to-end ML workflows using MLOps practices, collaborate cross-functionally, mentor peers, and drive ML engineering best practices and strategic initiatives.