Top Machine Learning Jobs in Malaysia

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Develop and support full-stack digital solutions for manufacturing and supply chain operations. Responsibilities include requirements analysis, software and database development, data integration and transformation, analytics, testing, troubleshooting, cybersecurity and governance compliance, architecture evaluation, and project leadership. The role partners with cross-functional teams to automate workflows, improve operational performance, and deliver scalable data-driven applications, while occasionally mentoring less experienced engineers.

Troubleshoot, install, commission, qualify, modify, automate, and continuously improve precision manufacturing equipment. The role performs root-cause analysis, interprets CAD and technical drawings, optimizes processes for yield and throughput, supports mechanical assembly and maintenance, develops safety procedures and technical documentation, trains technicians, and manages equipment improvement projects. AI/ML literacy is preferred for predictive maintenance, defect detection, and process optimization.

Develops, optimizes, qualifies, and improves substrate manufacturing processes for stable, high-quality output. Monitors chemical, mechanical, and optical parameters; troubleshoots equipment and process deviations; conducts root-cause analysis; improves yield, throughput, and quality; develops documentation and safety standards; trains technicians; and supports substrate characterization, manufacturing capability development, and process improvement projects.

Leads electrical energy studies, energy audits, power quality assessments, and system evaluations for industrial customers across Southeast Asia. Analyzes field measurements and operational data, identifies efficiency and reliability improvements, quantifies business benefits, prepares technical reports and proposals, and presents recommendations to customers. The role also develops energy management, process control, asset monitoring, and digital solution opportunities while supporting sales, follow-on projects, and regional capability development.

Own the platform product roadmap for internal tools used by sales, support, operations, and moderation teams. Lead AI-driven automation, agents, copilots, and productivity improvements while measuring efficiency and quality gains. Also oversee reliable, compliant checkout and billing, plus integrations across Mudah, third-party services, and Carousell Group. Partner with engineering, finance, payment providers, and cross-functional stakeholders to build scalable, reusable platform capabilities.

Supports commercial technology and data products across net revenue management, trade promotion, pricing, and in-store execution. Analyzes market, customer, and product data; translates initiatives into requirements and user stories; manages backlog contributions; supports Agile delivery, testing, release planning, dashboards, adoption tracking, governance, and risk management. Collaborates with commercial, design, technical, and data teams to validate solutions and communicate insights.

Combine supplier quality engineering with data analytics to build ELT pipelines, validate data, create automated Spotfire/Power BI dashboards, perform statistical modeling to monitor and predict manufacturing variances, and drive continuous improvement with supplier and internal teams. Provides rotational weekend support.

Lead supplier quality analytics for outsourced foundry, assembly, and test subcontractors. Build ELT pipelines, data validation, automated testing, and interactive dashboards (Spotfire/PowerBI). Use statistical modeling to track, predict, and resolve manufacturing variability, support continuous improvement, and provide weekend rotational support.

Lead supplier quality analytics for outsourced foundry, assembly and test partners. Build and maintain ELT pipelines, implement data validation and governance, create real-time dashboards (Spotfire/PowerBI), perform statistical analysis to detect drifts and defects, and drive continuous improvement and corrective actions. Support weekend rotation.

Develop and improve data science and machine learning models for marketing and consumer insights, including attribution, personalization, forecasting, experimentation, and marketing measurement. Prepare datasets, define evaluation metrics, support model deployment, and generate insights from media, pricing, promotions, and syndicated data. Collaborate with product owners, data engineers, and machine learning engineers; contribute to responsible AI governance, code reviews, reusable AI assets, and mentorship of junior team members.

Own the analytical framework for Zalora’s Revenue Office, including KPI governance, target setting, dashboards, customer analytics, forecasting, P&L management, and revenue-profit optimization. Lead performance reviews and cross-functional initiatives involving pricing, campaigns, CRM segmentation, and machine learning. Translate complex data into actionable commercial decisions while aligning Commercial, Campaign, Marketing, Merchandising, Data, and Technology teams.

Develop and productionize machine learning and data science prototypes into scalable, maintainable solutions. Responsibilities include designing, testing, deploying, optimizing, and maintaining ML systems across cloud and on-premises environments; applying statistical methods; improving engineering practices; and sharing expertise through internal knowledge exchange, conferences, and workshops.

Interns support AI, machine learning, computer vision, data analytics, and digital automation projects across the full lifecycle. Responsibilities include solution development, data preparation, testing, proof-of-concepts, user support, technology research, project coordination, requirements gathering, documentation, and stakeholder communication. The role provides exposure to technical and business workstreams while applying emerging technologies to manufacturing and business challenges.

Analyze semiconductor manufacturing, defect, and electrical data to identify yield limiters, improve process performance, conduct fault isolation, and develop yield models and measurement methodologies. Collaborate with design, test, and manufacturing teams to resolve quality issues and support advanced logic-node capabilities.

Intern will analyze NAND reliability and qualification data, execute wave tests, collect and analyze logs, support failure analysis, and develop AI-driven automation tools. Responsibilities include presenting engineering insights, creating technical documentation, maintaining source code, and demonstrating productivity improvements. The role may also involve developing a GenAI reliability engineering assistant for data analysis, failure identification, knowledge retrieval, and reporting.

Leads customer and portfolio analytics for corporate and commercial banking, translating complex data into growth opportunities, campaign strategies, and business insights. Develops dashboards, reports, automated processes, and performance monitoring tools; collaborates with technology and data teams to improve data quality and capabilities. Applies statistical analysis, predictive modeling, and machine learning to business challenges, presents recommendations to stakeholders, and mentors junior analysts.

Reviews financial services regulations and exchange rulebooks, assesses regulatory changes, and maintains auditable review records. Validates machine-learning topic classifications, provides labelled feedback, and helps maintain regulatory taxonomies. Compares platform rulebooks with authoritative sources to identify structural errors, missing provisions, duplication, and versioning issues. Performs quality assurance against development requirements and collaborates with product, engineering, and software teams to process new regulations and improve the service.

Write technically accurate case studies, articles, product explainers, launch materials, and social content for AI engineers, researchers, and technical leaders. Interview customers, partners, and internal experts; learn HUD’s platform and workflows; explain technical products and research clearly; support founder communications; manage content from ideation through publication; and improve content using reader and go-to-market feedback.

Leads strategic test planning and develops scalable automation frameworks for embedded, cloud, web, mobile, and API platforms. Oversees performance, security, UI, integration, and acceptance testing; integrates automated tests into CI/CD pipelines; evaluates testing tools and methodologies; applies AI to automation; and mentors engineers. The role requires cross-functional leadership, advanced problem solving, and end-to-end testing expertise for Motorola Solutions products.

Leads end-to-end device and system testing for embedded video products. Develops and maintains Python test automation, CI/CD pipelines, test tools, infrastructure, and documentation. Analyzes requirements, improves coverage, investigates false failures, manages defects, and validates issues with engineering teams. Supports AI model testing and automation enhancements, performs vehicle drive testing as needed, and provides technical leadership and mentorship.

Analyze complex datasets, develop and optimize statistical and machine learning models, and create AI solutions for business challenges. Clean and validate data, evaluate model performance, and collaborate with engineering, IT, and business stakeholders on deployment and improvement. Communicate analytical findings through reports, visualizations, and presentations while translating technical results into actionable recommendations. The role also requires staying current with data science, machine learning, generative AI, and responsible data practices.

Supports the COO Team with client profile and transaction reviews, control activities, process improvement and automation initiatives, and preparation of reports for senior stakeholders. The role requires analytical ability, attention to detail, communication skills, advanced Excel and VBA knowledge, and an understanding of core AI and machine learning concepts.

Develop machine learning and advanced analytics solutions for risk management, including predictive models, GenAI, agentic AI, data pipelines, dashboards, and automated reporting. Analyze complex datasets to identify emerging risks, control weaknesses, and non-compliance. Collaborate with stakeholders to deliver scalable analytical solutions, support model deployment and monitoring, and communicate insights to technical and executive audiences.

Lead the global strategy and roadmap for recommendations and personalization across three ecommerce platforms. Partner with data science, analytics, engineering, and regional teams to translate customer intent and machine-learning capabilities into scalable discovery experiences. Own experimentation, relevance, engagement, conversion, and commercial outcomes while balancing shared capabilities with local market needs.