Top Machine Learning Jobs in Malaysia

Develop, optimize, and maintain SSD test programs for high-volume manufacturing and NPI. Automate testing with scripts, enhance coverage, debug failures, collaborate with product/equipment teams, monitor metrics, manage test transfers, and mentor junior engineers.

Lead tactical industrial engineering for NAND/SSD manufacturing to optimize operations, align supply and capacity, manage NPI-to-HVM material flow, install processes/automation, investigate material/logistics issues, provide management updates, and coach a team focused on data-driven decisions.

18-month IT trainee program rotating across IT functions (Digitalization, Delivery, Data & Analytics, Cloud, Cyber Security). Support projects, prepare management reports, take independent tasks, receive mentoring, international exposure, and opportunities for permanent placement.

Perform exploratory and predictive analytics, build and evaluate machine learning and forecasting models, operationalize models with engineering partners, deliver executive dashboards and insights, ensure data governance and quality, and research emerging AI/analytics opportunities.

Lead roadmap, planning and delivery of ML/AI products for games. Scope ML efforts, track experiments and metrics, coordinate engineers and game teams, run Agile ceremonies, manage risks and stakeholders, and define evaluation plans for AI features.

Lead pre-sales and solution development for AI-driven customer engagements. Translate AI and ML capabilities into business value, build demos/POCs, support sales and architecture activities, engage C-level stakeholders, mentor technical teams, and collaborate with partners to create profitable, cross-practice solutions.

Lead AI transformation across Commercial: identify, prioritize, and deliver AI initiatives (forecasting, pricing, personalization, copilots, automation) that drive revenue, productivity, and data-driven decisions; translate business problems into scalable AI solutions; partner with Technology, Legal, Risk, and Data teams; build AI literacy and lead an execution-focused team.

Develop and deliver data analytics tools, algorithms, and methodologies to translate manufacturing data into insights for factory yield and process engineering. Apply predictive modeling, clustering, anomaly detection, time-series analysis, and ML frameworks to support engineers in semiconductor manufacturing.

Designs and applies statistical methods and predictive models to analyze manufacturing and business data, identify variation and patterns, create reports and dashboards, support cross-functional decision-making, and advance analytics infrastructure and data integrity.

The Data Annotator is responsible for labeling datasets, reviewing annotations for quality, collaborating with AI teams, and meeting annotation targets.

Lead strategy and execution for fraud risk management across the platform. Develop detection and prevention frameworks, optimize transaction screening, partner with Compliance, Data Science, Engineering and Product, oversee KPIs and vendor costs, lead a risk strategy team, and pilot AI/LLM-driven tools to enhance detection while enabling business growth and regulatory alignment.

Lead the core verification engine for global address and contact verification: drive discovery, define product strategy, partner with engineering and data science to improve accuracy, latency, throughput and resilience, productise AI/ML components responsibly, engage enterprise customers, run experiments and measure outcomes (conversion, match rates, cost), and deliver platform capabilities (APIs/SDKs, observability, SLAs) at scale.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

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 Virtual Factory systems and advanced analytics to optimize semiconductor manufacturing. Implement MES/IIoT integrations, dashboards, SPC/OEE analysis, root-cause investigations, and cross-functional continuous improvement to improve productivity and equipment utilization across global sites.

Lead employer outreach and strategic communications for enterprise programmes: design targeted engagement campaigns, develop content assets, leverage data and analytics (Enterprise360/CRM) to personalise messaging, measure campaign performance, build partnerships with industry bodies, and manage flagship events to increase employer awareness and adoption of workforce development initiatives.

Design, develop, test, integrate and maintain embedded firmware for enterprise HDDs. Implement drivers, data structures, algorithms and data path code (C/C++/Python). Work with SAS/SATA/PCIe interfaces, collaborate across hardware and software platforms (Windows/Linux), produce design documents, run CI/unit tests, and lead technical investigations to resolution.

Design, develop, test, integrate, and maintain firmware for enterprise HDDs. Implement data structures, algorithms, drivers and data paths in C/C++ and Python. Work with SAS, SATA, PCIe interfaces, collaborate across hardware and OS platforms (Windows/Linux), create design documents, run technical investigations, and follow unit test/CI best practices.

Design, develop, test, integrate, and maintain firmware for enterprise HDDs. Implement data structures, algorithms, drivers, and data paths in C/C++ and Python. Work with SAS, SATA, PCIe interfaces, collaborate across hardware and software, create design documents, and participate in technical investigations and CI-driven testing.

Support day-to-day business activities by gathering user requirements, analyzing data, creating documentation, and assisting in AI-related projects for a smoother communication between business and development teams.

Perform portfolio analytics and scorecard model development for capital and provisioning. Conduct Basel EL and RWA analysis, regulatory stress testing, forecasting, reporting, dashboard development and automation. Support systemisation, UAT/regression testing, stakeholder engagement and continuous process improvements using Python and visualization tools.

Develop, review and monitor credit rating models for the wholesale banking portfolio. Work with large datasets, perform model development, testing, documentation, UAT, and regulatory submissions. Produce performance monitoring reports, engage business experts for insights, and improve model monitoring and automation.

Lead AI and automation product initiatives for Seller Center, partnering with ML, engineering and regional teams to discover, design, validate and launch AI-driven features. Use qualitative and quantitative signals to prioritize work, run model and feature evaluations (A/B tests, shadow/offline tests, cohort analysis), communicate trade-offs to stakeholders, and ensure cross-market alignment and operational scalability.

Support the Polish Engineering team by assisting with development and implementation of manufacturing automation, programming and testing automated systems, collecting and analyzing process data, troubleshooting issues, documenting procedures, and researching emerging automation and data science technologies.

The Data Analyst role involves annotating emails, identifying malicious URLs, labeling data for AI training, ensuring process adherence, and supporting project management KPIs.