Top Machine Learning Jobs in Malaysia

The Director of Credit Risk Business Development will partner with clients to drive analytics and credit risk strategies, lead sales initiatives, and ensure successful analytics project implementations while achieving sales targets.

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.

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.

Oversee equipment preventive maintenance, set up and buyoff for form-factor conversions, install and propagate new equipment, troubleshoot major equipment issues, manage spare parts purchasing, train on SOPs and machine operation, lead continuous improvement projects, and follow OSHA safety standards. Use PLC/CTC/C++/Python and control systems for programming and troubleshooting.

Analyze PB-scale trading, transactional, operational and customer data; build visualizations, ML models and experiments; translate findings into actionable recommendations for trading, operations, product and executives in a fast-paced environment.

Design, build, and maintain backend APIs and services for a real-time supply chain visibility platform. Own system architecture, real-time event ingestion, data normalization, ML integration, monitoring, and production debugging while collaborating with Product and Data Science to deliver scalable, high-availability features.

Design, develop, and manage large-scale search and content recommendation systems. Apply ML-based personalization to improve content matching and distribution. Lead core recommendation module development, define success metrics, and collaborate with content, product, and business teams to drive AI product upgrades and better user and business outcomes.

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.

Lead design and management of search and content recommendation services and models. Build personalized recommender systems using ML/AI, define success metrics with product and business teams, drive core module development, and translate PB-scale data insights into measurable product impact.

Design, build, and manage large-scale search and content recommendation systems using machine learning and personalization techniques. Collaborate with content, product, and business teams to define success metrics, drive AI product improvements, and maximize content value and user impact.

Early-career Performance Engineer in the Binance Accelerator Program. Perform hands-on performance testing and tuning, design AI-powered test strategies using LLMs and ML, build AI-driven anomaly detection and bottleneck analysis tools, research new AI technologies, and improve reliability of large-scale distributed systems.

Design, back-test and implement pricing, risk management, and agency trading strategies; collaborate with developers to integrate models into the trading platform; participate in product ideation, modeling, parameter tuning, and risk evaluation.

Provide advanced technical support for escalated customer issues, analyze interactions to identify trends, collaborate with engineering/product teams, document resolutions, create knowledge base content, mentor junior staff, and use data analytics to improve support performance and customer satisfaction.

Provide mid-level technical support for Zebra products by troubleshooting issues, managing support tickets to meet SLAs, collaborating with cross-functional teams, creating training for junior staff, and contributing to process and product improvements.

Lead qualification of manufacturing ramps to high volume, set inspection and testing, run audits, manage excursions and MRBs, drive supplier and process improvements, represent quality in product development, and use statistics and machine learning to analyze data for disposition and reliability optimization.

Write and edit technical and thought-leadership content about AI, ML, reinforcement learning, robotics, and autonomous vehicles. Research projects, interview stakeholders, produce case studies, long-form articles, and explainers, optimize for SEO and readability, and collaborate with Growth, Marketing, and technical reviewers to publish polished content.

Build and maintain user tagging and profiling systems, analyze large-scale behavior data, perform feature engineering and exploratory analysis, support cross-functional teams for segmentation, monitor tag effectiveness, detect anomalies and fraud patterns, and improve data methodologies to enable risk control and personalized services.

Develop and deploy fault detection, predictive analytics, APC and ML models for manufacturing. Perform EDA, validate data quality, monitor model performance, collaborate with cross-functional teams, and lead continuous improvement to improve yield, cycle time, and equipment performance.

Lead product development for iPiD's Global Validate service, managing integrations to new countries/data providers, delivering API features with engineering and BD, analysing payment data and schemes, supporting clients and reports, and aligning cross-functional teams to launch and optimise product enhancements.

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.

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 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.

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.

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.