Top Machine Learning Jobs in Malaysia

Research AI, machine learning, robotics, autonomous vehicles, and data annotation topics, then create technical blogs, case studies, explainers, whitepapers, and thought leadership content. Translate complex concepts into clear, commercially relevant narratives for enterprise audiences. Collaborate with technical, Growth, and Marketing teams, incorporate editorial feedback, optimize content for readability and SEO, source supporting research, and maintain consistent messaging across digital channels.

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

Define technology transfer roadmaps and equipment/configuration for modules. Extract insights from structured and unstructured manufacturing data using statistics and machine learning. Drive low-yield analysis, yield improvement, and continuous improvement programs in startup and high-volume semiconductor manufacturing. Perform quality and reliability risk assessments for materials and process changes while collaborating with internal and external stakeholders.

The Senior Gen AI Engineer leads the design and strategy for Generative AI use cases, focusing on user research, product management, and collaboration with cross-functional teams to drive AI innovations and solutions.

This role involves leading AI use case discovery and strategy, user research, product concepting, and prioritization of AI initiatives, ensuring alignment with customer needs and business value.

The AI/ML Engineer develops and integrates AI models into production systems, optimizing performance and supporting project teams with leadership and mentorship.

Perform remote part-time data tasks to improve Malay AI content, including data collection, evaluation, annotation, pairwise comparisons, counting, and object tagging across audio, video, images, and collected data.

Develop, implement and maintain credit risk models (scorecards, IRM, IFRS9 ECL, stress testing, economic capital, ML). Monitor model performance, manage governance and validation, engage auditors/regulators, and deliver model outputs for credit decisioning, allowance and capital assessment.

Leads global technical training, competency management, LMS governance, process standardization, audit readiness, and workforce development across semiconductor manufacturing sites. Partners with training teams, engineering, HR, and subject matter experts to develop curricula, manage qualification frameworks, monitor compliance dashboards, identify capability gaps, and implement corrective actions. Oversees cross-functional training projects and supports digitalization, automation, continuous improvement, and learning-system enhancements across global fabs.

Lead and architect Internal Audit for an AI-driven, regulated fintech. Build a risk-based audit strategy and team; oversee financial, operational, technology, AI, cybersecurity, regulatory, and third-party assurance; implement continuous monitoring and automated testing; assess AI governance and model risk; and provide independent, evidence-based reporting to the Board, Audit Committee, and regulators.

Lead and build Deriv’s technology-centric Internal Audit function across finance, operations, technology, AI, cybersecurity, regulatory, and third-party risk. Develop risk-based audit strategies and plans, implement continuous control monitoring and automated testing, assess AI governance and model risk, review IT and cloud controls, and provide independent reporting to the Board, Audit Committee, and regulators. Recruit and develop a technically fluent team while maintaining audit independence and delivering commercially grounded recommendations.

Leads finite capacity modeling, scenario analysis, and production planning across multiple manufacturing value streams. Aligns capacity with demand forecasts, supports new product introductions and factory ramps, identifies bottlenecks, and communicates risks and recommendations to leadership. Drives continuous improvement using Lean Six Sigma, industrial engineering methods, data analysis, and optimization of throughput, utilization, staffing, shifts, and capital investments. Partners cross-functionally with operations, supply chain, engineering, suppliers, and senior leaders.

Supports data science and analytics solution development that drives business growth, customer experience, productivity, and efficiency. Responsibilities include delivering analytics workplans, developing statistical, predictive, segmentation, and propensity models, creating reusable best practices, supporting business decisions, and collaborating with multidisciplinary teams. The role requires programming-based analytics expertise, machine learning knowledge, strong analytical and problem-solving skills, business acumen, and project management capabilities.

Sustain and improve semiconductor production processes through SPC/FDC monitoring, troubleshooting, CPK improvement, recipe development, process qualification, and tool release. Lead continuous improvement initiatives using statistical analysis, big data analytics, AI/ML, and structured problem-solving to improve wafer yields, productivity, cost, capacity, and process robustness. Collaborate with cross-functional teams, fabs, and equipment suppliers, while training and guiding Associate Engineers.

As an AI Data Specialist, you will support AI-generated content improvement in Chinese Simplified through tasks like data collection, evaluation, and annotation.

Designs and executes cybersecurity system integration tests for software and hardware, develops automation scripts and maintains test infrastructure, troubleshoots failures, manages defects, and integrates AI/ML to improve automation solutions while documenting processes and collaborating across engineering teams.

Provides technical consulting for AML, sanctions screening, and third-party risk solutions across APAC. Leads RFPs, sales engagements, client implementations, API integrations, data pipelines, analytics, reporting, and risk decisioning initiatives. Advises customers on data architecture, modeling, transformation, and enrichment while serving as a technical SME and customer advocate. Partners with sales, product, and delivery teams, presents at industry events, and monitors regulatory, technology, and competitive developments.

Designs, develops, validates, and deploys AI and machine learning solutions, including GenAI copilots, recommendation engines, RAG applications, and agentic AI workflows. Analyzes structured and unstructured data, creates predictive and generative models, develops visualizations and data narratives, and partners with cross-functional teams to deliver measurable business value.

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 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.

Analyze large-scale on-chain data to detect anomalous transactions, develop detection mechanisms and risk monitoring frameworks, apply supervised and unsupervised ML, identify malicious accounts via community-discovery algorithms, and design integrated on-chain/off-chain prevention and control systems.

Lead engineering projects, automation and digitization, new product qualification, and machine/process reliability. Manage budgets, timelines, root-cause troubleshooting, maintenance strategy, and integration of advanced manufacturing technologies. Mentor and develop engineering team, ensure safety and compliance, and coordinate with regional/global stakeholders to drive productivity and operational excellence.

Design and develop custom SAP applications using ABAP (RAP/OO), CDS Views, SAP BTP and Fiori/UI5. Embed AI capabilities (SAP AI Core, Joule, generative and predictive models) into processes, prototype AI use cases, support integration understanding, apply Agile and CI/CD, and continuously improve solution quality and maintainability.